Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicant
This communication is in response to the amendment filed 10/27/2025. Claims 1, 5, 9, and 11 have been amended. Claims 1-11 remain pending and have been examined.
Response to Arguments
A. Applicant’s arguments with respect to the rejection of claims 1-11 under 35 USC 101 have been fully considered but are not persuasive.
Applicant argues that the claimed method “clearly requires secure decoding, validation, mapping, and storage of medical imaging data using computing systems, decryption algorithms, predefined standards, and structured business object logic none of which can be practically performed mentally or manually.” Examiner respectfully disagrees.
Applicant points to paragraphs 17-19 and 27 of the specification in asserting that the step of receiving the encoded medical imaging data “is performed by a receiver computing system configured to ingest machine-readable medical imaging data that is already encoded and pre-validated using standardized medical formats such as XML, or JSON” and that “this operation involves system-level network communication, parsing of encoded files, and compliance checks against predefined medical data standards.” However, the claims do not recite the “machine-readable” format or predefined standards as being XML or JSON formats. The term “machine-readable format” does not require that the format be exclusive to computers or that it could not be read or validated by a human. Rather, it only recites that the format could be readable by a machine. Likewise, the claim does not limit “predefined medical data standards” or what constitutes the act of “validating” in any manner which would preclude a human from looking at the imaging information and confirming that it complies with some standard.
Applicant cites paragraphs 30-33 as requiring the use of “software based encryption keys and decryption logic” which are “designed to work with specific data encryption protocols.” Examiner notes that paragraphs 30-33 do not describe software based encryption keys and decryption logic, and even so, the claims do not recite or require the use of “software based encryption keys and decryption logic.” While the claims are construed in light of the disclosure, limitations are not imported into the claims. Examiner notes that Applicant should amend the claims to incorporate such subject matter in order to have the claims construed as limited thereto.
Likewise, the claims do not recite or require that the predefined medical imaging standards be DICOM schemas, JavaScript Object Notation (JSON), and Extensible Markup Language (XML). Examiner notes however, that each of these formats is fully readable by a human, and a human would be capable of confirming whether received information conformed to one or more of these formats. Examiner similarly disagrees with Applicant’s assertion that “[t]his validation is not organizational or administrative in nature, but rather a technical compliance check requiring software-driven schema parsing, rule-based evaluation, and structured error detection.” As noted above, no limitation is placed on what constitutes “predefined standards” which would require software for validation. As-written, the claim currently only requires any form of validation against any form of predetermined standard for imaging data.
Applicant further argues starting on page 13 that the step of mapping the decoded medical imaging data based on one or more business objects “refers to the automated mapping of the validated and decoded medical imaging data to one or more business objects (may include, but are not limited to, Patient details, protocol parameters, and reconstruction parameters) associated with the receiver system.” Applicant asserts that “this is not a manual categorization task, but a technical operation driven by software-based rules and data structures” and that “[t]he mapping is executed within the receiver system and thus are entirely computational and not performable manually or mentally.” Examiner respectfully disagrees. The claim does not limit the manner in which the medical imaging data is mapped to “business objects” to a mechanism requiring a computer, and while the claim does not limit the recited business objects to patient details, protocol parameters, and reconstruction parameters, a human would be able to map received imaging data to these categories. The use of a computer in the form of a system does not preclude the mapping function itself from being performable by a human.
Similarly, the claim does not limit the scope of “reconstruction data,” or the function of generating reconstruction data, to acts which require a computer or exclude reformatting or manual configuration. Paragraphs 32, 48, and 57 describe the reconstruction data as having fields corresponding to various categories of information such as patient name, the institution where the source system is installed, prescribed medicine, and a certified technician. These fields are checked to make sure that they were not impermissibly changed, such as the data for patient name no longer matching the correct patient name, and may be edited by a user as part of generating the reconstruction data. For example, paragraph 57 states
“…data may be prepared with new parameters for image reconstruction. For example, the decoded medical imaging data may be extracted, and a user input may be received to prepare the data with new parameters. The data with new parameters may also be referred to as reconstruction data. The set of variable fields in the decoded medical imaging data may be changed based on the user input. For example, the input may include values corresponding to at least one of a size parameter and an orientation parameter of an image to be reconstructed.”
These steps do not require hardware-enabled image processing or geometric transformation algorithms as argued by Applicant, and steps such as a user inputting a size parameter or orientation parameter for how an image should be displayed may be manually performed.
Examiner again highlights that the claims currently do not require the subject matter from the specification argued by applicant, and notes that Applicant should amend the claims to incorporate the subject matter argued from the specification if Applicant wishes to have the claims construed as requiring those elements for the validation, mapping, and other steps.
Applicant further argues that the claims recite elements integrate any abstract idea into a practical application and “yield a concrete and tangible improvement in the security, interoperability, and adaptability of medical imaging systems by automating the end-to-end process of encoding, transmitting, validating, classifying, and reconstructing imaging data across heterogeneous platforms.” Examiner respectfully disagrees.
Applicant asserts that “[t]he claimed method is deeply rooted in technical medical imaging data handling and system-level interoperability,” citing to paragraphs 52-56 and Figure 7 as showing that the receiver system and source system are not merely generic computing devices. However, Examiner initially notes that paragraph 61 expressly states that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer,” that “[t]he computing system 800 may represent, for example, a user device such as a desktop, a laptop, a mobile phone, personal entertainment device, DVR, and so on, or any other type of special or general-purpose computing device as may be desirable or appropriate for a given application or environment” and “may include one or more processors, such as a processor 801 that may be implemented using a general or special purpose processing engine such as, for example, a microprocessor, microcontroller or other control logic. While Applicant argues that the claims recite operations which “reflect domain-specific logic and structured protocols that are essential for secure and compliant imaging workflows not mere data movement or storage,” linking the use of a judicial exception to a particular technological environment or field of use is not sufficient to integrate an abstract idea into a practical application.
The steps of mapping and storing the information fall within the scope of the abstract idea, and characterizing them as “executed based on rule-driven logic and object models” is not sufficient to establish that they could not simply be performed by a human given the high level of generality with which they are currently recited.
Applicant further argues that “the reconstruction system prepares data using size and orientation parameters provided by a user, then validates this reconstruction data against clinical rules and performs AI-driven reconstruction of diagnostic images” and that “[t]his process involves structured computation based on both fixed and variable fields in the imaging data and solves a practical technical challenge: enabling image reconstruction even when source and receiver scanners differ in configuration or capability.” Examiner respectfully disagrees. Examiner initially notes that the claims do not recite the use of any form of “AI-driven reconstruction of diagnostic images.” Claim 1 for example, recites “generating, by the receiver system, reconstruction data based on the stored decoded medical imaging data and an input received from a user, wherein the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image.” As noted above, paragraph 57 describes the reconstruction data as data containing new parameters such orientation or size information received from a user. While claim 1 does not recite actually reconstructing images, Examiner notes that the recitation in claim 6 of “generating a reconstructed image based on the validated reconstruction data, wherein the reconstructed image comprises information associated with the source system and the receiver system” is recited broadly and does not actually require computational generation of new images. Given that the reconstructed image data may be data fields specifying orientation or size, generating a reconstructed image reasonably encompasses orienting or resizing the image. Examiner notes that Applicant should incorporate the argued subject matter into the claims in order to have them construed accordingly under Step 2A Prong 2.
With respect to Applicant’s argument that “the claimed invention addresses a well-recognized technical problem in medical imaging systems: how to transfer and reconstruct imaging data securely and accurately across heterogeneous platforms” and assertion that the improvement enables transmitting raw medical imaging data rather than DICOM images “critical to enabling accurate image reconstruction across devices,” Examiner again notes that the argued subject matter is not reflected in the actual limitations of the claims. Under Step 2A Prong 2, any asserted improvements to technology or a technical field must be reflected in the limitations of the claims themselves. Currently, the claims do not recite any transmission of “raw” imaging data and would encompass transmitting images in DICOM format. Applicant should incorporate the argued subject matter into the claims in order to have them construed accordingly under Step 2A Prong 2.
Examiner accordingly respectfully disagrees with Applicant’s assertion that the claims are analogous to those in DDR Holdings LLC. While the claims are recited as incorporating computing elements, the computing elements are recited at a high level of generality and disclosed as encompassing generic computer hardware (see e.g. paragraph 61). The use of generic computing elements to perform the functions such as transmitting, decoding, validating, and mapping the imaging data only amounts to instructions to implement the function using a generic computer, and the recited functions themselves do not currently reflect the argued technical improvements.
Applicant argues starting on page 23 that the claims amount to significantly more than a judicial exception, asserting that “[w]hen the claims are properly considered as a whole, they reflect a specific and nonconventional technological solution to a longstanding problem in the field of medical imaging: how to securely transmit, validate, classify, and reconstruct raw medical imaging data between heterogeneous imaging systems.” Examiner respectfully disagrees.
Applicant asserts that “[t]he claimed invention improves upon traditional imaging data workflows that often rely on sending static DICOM images between systems an approach that leads to image inconsistencies due to hardware differences, loss of reconstruction flexibility, and system compatibility issues,” and cites paragraphs 52-60 as describing “the present invention provides a secure and interoperable pipeline that enables systems to exchange raw imaging data, validate it using predefined medical standards, and then reconstruct the image using system-specific configurations and user-defined parameters such as size and orientation.” However, the limitations of present claims do not reflect the argued improvement. As noted above, the claims do not recite sending “raw” imaging data or that any information beyond standard DICOM image data is received or transferred between systems.
The claimed steps, including receiving medical imaging data in a “machine-readable format” having been validated “based on a plurality of predefined standards,” decoding the encoded medical imaging data using a decryption technique, validating the decoded medical imaging data “based on the plurality of predefined standards,” mapping the decoded medical imaging data “based on one or more business objects” associated with the receiver system, storing the decoded medical imaging data “based on one or more configurations of the receiver system,” and generating reconstruction data “based on the stored decoded medical imaging data and an input received from a user,” are recited at a level of generality that does not capture or reflect the argued improvements. Examiner again notes that subject matter of the disclosure is not imported into the claims, and the claims at their current level of generality do not require the elements being relied upon by Applicant in support of the asserted improvement. Likewise, reconstruction of any imaging data is not recited as requiring any specific actions, and may encompass basic functions such as simply displaying static images in a particular orientation.
The above arguments apply to Applicant’s assertions on page 27 regarding processing of raw image data, “real-time input,” and “adaptive transformation.”
The rejection of claims 1-11 under 35 USC 101 is maintained.
B. Applicant's arguments with respect to the rejection of claims 1-11 under 35 USC 112(b) have been fully considered but they are not persuasive.
Applicant argues starting on page 29 that the recitation of “configurations of the receiver system” is not indefinite based on the specification and drawings. Examiner respectfully disagrees. Applicant cites paragraph 4 of the specification as stating that
“Paragraph [0004] of as filed specification explains that medical imaging data can be acquired at one location and reconstructed at a different location using a separate system possibly involving a scanner from a different model. This capability enables image reconstruction without repeating the scan or reapplying contrast material. To achieve this, the receiver system must be capable of interpreting and processing incoming data in accordance with its own operational and reconstruction protocols. These internal rules, logic, and parameter sets are collectively described as "receiver system configurations.””
However, the description in paragraph 4 does not reflect Applicant’s assertions. Paragraph describes transferring medical imaging data securely from a source system to a receiver system as well as using transferred data to reconstruct medical images “with required new parameters,” but does not describe a receiver system having its own operational and reconstruction protocols or forms of internal rules, logic, and parameter sets.
Applicant cites Figure 2 and paragraph 23 as illustrating structural elements including modules for performing the receiving, decoding, validation, and mapping functions as well as a data store for storing the image data, and Figure 7 as illustrating the steps of mapping and storing. However, none of these portions of the disclosure address anything which could be construed as “receiver system configurations” used to determine how the imaging data is stored. While element 713 in Figure 7 shows a step of storing the data, no further detail is provided. Likewise, paragraph 23 only provides that “stores the data as decoded medical imaging data 206 which may be used further (for example, for image reconstruction).” While paragraph 27 states that “[i]n some embodiments, for mapping, the mapping module 204 may determine compatibility of the decoded medical imaging data with the receiver system configurations,” it does not provide any further description of what those receiver system “configurations” actually are, or storing the data “based on one or more configurations of the receiver system.”
Applicant asserts on page 30 that the mapping module “ensures that the data is interpreted properly based on the receiver's own setup” and that “[t]hese configurations include the receiver's expected formats, protocol parameters, business rules, and operational constraints, and may differ from those of the source system.” However, this assertion is not supported by the specification. Neither paragraph 27 nor other portions of the specification describe “expected formats,” “protocol parameters,” “business rules,” or “operational constraints,” or that such types of information would be used in storing the imaging data. While “protocol parameters” are mentioned in paragraph 27, they are described as one potential form of business object, which is a different term recited in the claim and both recited and described as part of the mapping function.
Paragraph 60 similarly does not reflect Applicant’s assertion on page 31 that “[r]ather than exchanging final DICOM images which can be inconsistent across systems the invention transmits raw imaging data that the receiver can reconstruct using its own configurations and logic.” While paragraph 60 states that “[i]t should be noted that there may be a difference in DICOM images scanned by two different scanners (scanned at the same time for the same patient but due to different system configurations),” it does not provide any clarification on what those system configurations actually encompass.
Applicant’s statement that “[t]hese configurations govern how the system validates, interprets, maps, stores, and reconstructs data using different scanners or institutional policies” lacks support in the disclosure given that no description is provided of configurations which govern how the system “validates, interprets, maps, stores, and reconstructs data using different scanners or institutional policies.” Applicant’s assertion that “the term "receiver system configurations" refers to the technical rules, constraints, and expectations that define how the receiver system processes imaging data” is likewise not reflected in the actual language of the disclosure.
Applicant’s arguments amount to describing the purpose of the claimed system and method and how there can be differences between a source and a receiver system, but do not actually link the term to a corresponding description which would allow one of ordinary skill to understand what particular information is encompassed by the term. Broad and generalized assertions such as that the term “refers the technical rules, constraints, and expectations that define how the receiver system processes imaging data,” without corresponding description in the specification or drawings, support the conclusion that one of ordinary skill would not understand what would fall within the scope of the term or the storage of imaging information based thereon.
The rejection of claims 1-11 under 35 USC 112(b) is maintained.
C. Applicant's arguments with respect to the rejection of claims 1-11 under 35 USC 103 have been fully considered but they are not persuasive.
Applicant argues starting on page 33 that the applied Choudhury and VanNostrand references do not teach or suggest “upon successful validation, mapping, by the receiver system, the decoded medical imaging data based on one or more business objects associated with the receiver system.” Examiner respectfully disagrees.
Applicant asserts that Choudhury does not disclose or suggest “mapping decoded medical imaging data to business objects such as patient records, protocol preferences, or reconstruction settings (refer paragraph [0027] of as filed specification) after validation.” However, Examiner notes that the claims do not recite business objects as including patient records, protocol preferences, or reconstruction settings. While terms within the claims are construed in light of the disclosure, specific limitations are not imported into the claims. Furthermore, Choudhury is not relied upon to teach performing the mapping “after validation.” As noted below, VanNostrand is relied upon to teach this limitation. While Applicant asserts that the focus of Choudury “is on preprocessing and transmission, not semantic or contextual mapping,” Applicant does not provide further arguments addressing the specific limitations within the claims it is relied upon to teach.
Applicant further argues that VanNostrand discloses transforming XML-based clinical data into formats such as DICOM or HL7, but that the transformations are applied “to structured XML documents (e.g., patient demographics or lab results) and not raw imaging data.” However, Examiner notes that the claims do not recite “raw” imaging data, and is instead relied upon to teach a receiving system mapping imaging data after validation. Examiner additionally notes that paragraph 18 of Applicant’s specification discloses a machine-readable format of the imaging data as including XML, and that Figure 8 of VanNostrand shows an example XML clinical data file being a clinical imaging study file (see also VanNostrand paragraph 20).
Examiner further respectfully disagrees with Applicant’s assertion that Choudhary “stops at protocol conformance and transmission and does not describe alignment of decoded imaging data with internal entities (business objects) of the receiver system.” Initially, Examiner notes that the claims recite mapping the decoded medical imaging data “based on one or more business objects associated with the receiver system,” and do not recite “alignment of decoded imaging data with internal entities.” As cited, Figure 9 and paragraphs 25, 37, 41, 43, and 44 of VanNostrand describe converting the decrypted data from a format that does not conform to the medical imaging protocol to a first format which does conform to the medical imaging protocol.
With respect to Applicant’s assertion that “VanNostrand applies business-rule-based transformation only to metadata (XML clinical data), and does not involve raw imaging data, image reconstruction, or mapping to operational constructs such as reconstruction protocols or scan settings,” Examiner again notes that the claims do not recite “raw imaging data” or “operational constructs such as reconstruction protocols or scan settings.” VanNostrand is relied upon to teach a receiving system mapping imaging data after validation, and includes imaging data in XML format. Examiner again points to paragraph 18 of Applicant’s specification discloses a machine-readable format of the imaging data as including XML, and that Figure 8 of VanNostrand shows an example XML clinical data file being a clinical imaging study file (see also VanNostrand paragraph 20).
Applicant further argues starting on page 35 that there is no motivation to combine the systems of Choudhury and VanNostrand. Examiner respectfully disagrees. Applicant asserts that the combination “would not be a routine modification,” and lists “decoding and validation of raw imaging data based on receiver-side rules, a mapping module capable of associating incoming imaging data with predefined business entities (e.g., data models, clinical workflows, or reconstruction preferences), receiver-specific logic to execute reconstruction or further processing based on that mapping.” Examiner again notes that the claims do not recite raw imaging data or associating incoming imaging data “with predefined business entities (e.g., data models, clinical workflows, or reconstruction preferences).” Applicant does not provide further reasons why the listed functions support a conclusion that it would not have been obvious to combine the Choudhury and VanNostrand references.
Applicant further argues starting on page 36 that the cited references fail to teach, disclose, or suggest “generating, by the receiver system, reconstruction data based on the stored decoded medical imaging data and an input received from a user, wherein the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image.” Examiner respectfully disagrees.
Applicant asserts that Gendron does not disclose or suggest generating reconstruction data at the receiver system based on decoded image content and user input such as size or orientation parameters, and that Gendron “does not perform reconstruction operations and does not interpret image data beyond DICOM-level identifiers or routing metadata.” Examiner respectfully disagrees that Gendron does not teach or suggest generating reconstruction data based on stored medical imaging data and an input received from a user. As cited, Figure 5 and paragraphs 74, 75, 77, 78, and 81-84 describe retrieving and translating particular DICOM imaging data, construed as generating reconstruction data, based on stored study data and the inputted request from a user. While Gendron is not relied upon to teach actually performing reconstruction of the medical imaging data, Examiner notes that paragraphs 85 and 86 describe presenting the data to an operator at a view station. Furthermore, Examiner maintains that using stored imaging data to generate data used for reconstruction based on an inputted request by a user teaches generating reconstruction data based on the stored data “and an input received from a user.” Gendron is not relied upon to teach the input comprising a size parameter or an orientation parameter.
Applicant then further asserts that “Omernick only teaches post-acquisition image orientation metadata adjustments or header modifications, rather than dynamic reconstruction of image data using the stored image payload in combination with user-supplied reconstruction parameters.” However, Examiner maintains that Omernick teaches a user inputting an orientation parameter of an image which is used to generate reconstruction data (See e.g. Omernick Figure 3, [17], and [42]-[44] describing a user entering a value for image orientation which is then used to generate the reconstructed image based on the orientation). Applicant does not provide explanation as to why receiving a user input of an orientation parameter of an image for “post-acquisition image orientation metadata adjustments or header modifications” would fail to teach an input comprising values corresponding to an orientation parameter of an image which is used to generate reconstruction data of the image. Examiner notes that the claim does not recite the “reconstruction data” as being the actual reconstructed image presented to a user, but rather as information used to then generate the reconstructed image (see e.g. Claim 6).
With respect to Applicant’s assertion that “Gendron's system is focused on routing and prefetching storage assets for availability and network optimization, not on image processing or user-driven reconstruction at the receiver end,” and that “Omernick applies user preferences to adjust orientation metadata for consistent image display not to trigger image reconstruction at the receiver system using decoded medical imaging data as an input,” Examiner again notes that Gendron is relied upon to teach generating reconstruction data based on stored medical imaging data and an input received from a user, and that Omernick is relied upon to teach a user inputting an orientation parameter which is then used as part of generating reconstruction data. Examiner again notes that the claims do not recite the user input as “trigger[ing] image reconstruction at the receiver system.” Rather, the claim recites a receiver generating reconstruction data based on 1) the stored decoded medical imaging data and 2) an input received from a user, and that the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image. The claim does not further limit what the user input does or when the user input is provided beyond its use to generate the reconstruction data and including values corresponding at least one of a size parameter and an orientation parameter of an image.
Applicant lastly argues that there is no motivation to combine the teachings of Gendron and Omernick to yield the claimed functions. Examiner asserts that the combination would require “A reconstruction engine embedded in the receiver system that can accept user-defined input parameters such as image size and orientation; Access to and processing of raw or decoded pixel data, not merely header fields or metadata; Reconstruction based on user input a function far beyond Gendron's routing or Omernick's header editing systems.” Examiner respectfully disagrees. Omernick expressly discloses a viewing system capable of reconstructing images using user-inputted parameters such as image orientation as well as access to and processing of image pixel data (see Omernic [18] and [42]-[44] as well as Figure 3 and [46]), and Applicant’s assertion regarding “Reconstruction based on user input a function far beyond Gendron's routing or Omernick's header editing systems” lacks nexus with the claims and disclosure. Applicant does not provide further clarification on how the asserted elements support a conclusion that a person of ordinary skill in the art would not be motivated to combine the relied upon teachings of Gendron and Omernick.
The rejection of claims 1-11 under 35 USC 103 is maintained.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-8 are drawn to a method, while claims 9-11 are drawn to a system, each of which is within the four statutory categories.
Step 2A(1)
Claim 1 recites, in part, performing the steps of:
receiving, by the receiver, encoded medical imaging data from the source, wherein the encoded medical imaging data comprises the medical imaging data in a machine-readable format and validated based on a plurality of predefined standards,
decoding, by the receiver, the encoded medical imaging data using a decryption technique,
validating, by the receiver, the decoded medical imaging data based on the plurality of predefined standards,
upon successful validation, mapping, by the receiver, the decoded medical imaging data based on one or more business objects associated with the receiver,
storing, by the receiver, the decoded medical imaging data in a data store associated with the receiver based on one or more configurations of the receiver, and
generating, by the receiver, reconstruction data based on the stored decoded medical imaging data and an input received from a user, wherein the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image.
These steps amount to a form of managing personal behavior or relationships or interactions between people, and therefore fall within the scope of a certain method of organizing human activity. Fundamentally the process is that of receiving, decoding, and validating medical imaging data according to a standard, and then storing the imaging data after mapping it to information categories (see e.g. [27] of Applicant’s specification describing “business objects”). These functions could be performed as part of individuals sending and receiving medical imaging data and storing that information based on categories set by the receiver.
Examiner also notes paragraph 18 of Applicant’s specification describing “machine-readable format” as including formats such as Comma-Separated Values, JavaScript Object Notation, and Extensible Markup Language, which are also human-readable.
Independent claim 9 recites similar limitations and also recites an abstract idea under the same analysis.
Step 2A(2)
This judicial exception is not integrated into a practical application because the additional elements within the claims only amount to:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
Claim 1 recites the additional elements of a) a receiver system recited as performing the functions of the receiver, and b) a source system recited as performing the functions of the source.
Claim 9 recites the additional elements of a) a processor recited as executing stored instructions to perform the subsequently recited functions, b) a memory recited as storing the instructions, and c) a source system recited as performing the functions of the source.
Paragraphs 17 and 23 describe source system 100 and receiver system 200, while paragraphs 35 and 36 state that source system 100 and receiver system 200 “may be implemented in programmable hardware devices such as programmable gate arrays, programmable array logic, programmable logic devices, or the like” or “implemented in software for execution by various types of processors” such as ASICs. Each of the receiver system, source system. Paragraphs 35 and 36 also describe the instructions as stored in memory devices and accessed by the processor.
Additionally, paragraphs 61-63 state that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer” such as desktops, laptops, mobile phones, or other general-purpose computers, and describe the computer system as employing microprocessors and various types of RAM, ROM, flash memory, and other memory types. The receiver system, source system, processor, and memory are each therefore construed as encompassing generic forms of computer processing and memory devices.
The above elements only amount to mere instructions to implement the functions of the abstract idea using computing elements as tools. For example, the receiver system and source system are each only recited at a high level of generality as used to perform functions such as receiving and validating the medical image data and are disclosed as encompassing generic computing elements, as are the recited processor and memory. These elements are therefore not sufficient to integrate the abstract idea into a practical application.
The above claims, as a whole, are therefore directed to an abstract idea.
Step 2B
The present claims do not include additional elements that are sufficient to amount to more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation of:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
As explained above, claims 1 and 9 only recite the receiver system, source system, processor, and memory as tools for performing the steps of the abstract idea, and mere instructions to perform the abstract idea using a computer is not sufficient to amount to significantly more than the abstract idea. MPEP 2106.05(f)
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
Depending Claims
Claim 2 recites generating, by the source, the medical imaging data in the machine-readable format by parsing medical imaging data, wherein the medical imaging data comprises a set of variable fields and a set of constant fields; validating, by the source, the medical imaging data based on the plurality of predefined standards; upon successful validation, by the source, encoding the medical imaging data using an encryption technique to generate the encoded medical imaging data; and transmitting, by the source, the encoded medical imaging data to the receiver. These limitations fall within the scope of the abstract idea as set out above.
Claim 2 recites the additional elements of a) the source being a source system and b) the receiver being a receiver system.
As cited above, paragraphs 17 and 23 describe source system 100 and receiver system 200, while paragraphs 35 and 36 state that source system 100 and receiver system 200 “may be implemented in programmable hardware devices such as programmable gate arrays, programmable array logic, programmable logic devices, or the like” or “implemented in software for execution by various types of processors” such as ASICs. Paragraphs 35 and 36 also describe the instructions as stored in memory devices and accessed by the processor.
Additionally, paragraphs 61-63 state that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer” such as desktops, laptops, mobile phones, or other general-purpose computers, and describe the computer system as employing microprocessors and various types of RAM, ROM, flash memory, and other memory types.
The receiver system and source system are each therefore construed as encompassing generic forms of computer processing and memory devices.
The above elements only amount to mere instructions to implement the functions of the abstract idea using computing elements as tools. Specifically, the receiver system and source system are each only recited at a high level of generality as used to perform functions such as validating and transmitting the medical image data and are disclosed as encompassing generic computing elements. These elements are therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claim 3 recites wherein the set of constant fields comprises at least one of text data and binary data corresponding to a patient, an imaging system, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician. These limitations fall within the scope of the abstract idea as set out above.
Claim 4 recites wherein the set of variable fields comprises at least one of text data and binary data corresponding to an examination parameter, a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, one or more examination rules and constraints, and additional examination data. These limitations fall within the scope of the abstract idea as set out above.
Claim 5 recites validating, by the receiver, the reconstruction data based on a plurality of predefined clinical rules and the set of constant fields. These limitations fall within the scope of the abstract idea as set out above.
Claim 5 recites the additional element of the receiver being a receiver system.
As cited above, paragraphs 17 and 23 describe source system 100 and receiver system 200, while paragraphs 35 and 36 state that source system 100 and receiver system 200 “may be implemented in programmable hardware devices such as programmable gate arrays, programmable array logic, programmable logic devices, or the like” or “implemented in software for execution by various types of processors” such as ASICs. Paragraphs 35 and 36 also describe the instructions as stored in memory devices and accessed by the processor.
Additionally, paragraphs 61-63 state that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer” such as desktops, laptops, mobile phones, or other general-purpose computers, and describe the computer system as employing microprocessors and various types of RAM, ROM, flash memory, and other memory types.
The receiver system is therefore construed as encompassing generic forms of computer processing and memory devices.
The above elements only amount to mere instructions to implement the functions of the abstract idea using computing elements as tools. Specifically, the receiver system is only recited at a high level of generality as used to perform the validation and is disclosed as encompassing generic computing elements. This element is therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claim 6 recites generating a reconstructed image based on the validated reconstruction data, wherein the reconstructed image comprises information associated with the source system and the receiver system. These limitations fall within the scope of the abstract idea as set out above.
Examiner notes that the source system and receiver system are not recited in the above limitations as performing any function, and are only recited as being associated with information comprised in the reconstructed image.
Claim 7 recites rendering an error with a reason of failure to the user, for each failed validation corresponding to the medical imaging data, the decoded medical imaging data, and the reconstruction data. These limitations fall within the scope of the abstract idea as set out above.
Claim 8 recites wherein storing the decoded medical imaging data comprises determining compatibility of the decoded medical imaging data with the receiver system configurations. These limitations fall within the scope of the abstract idea as set out above.
Examiner notes that the receiver system is not recited in the above limitations as performing any function, and is only recited as the object of the configurations used in determining compatibility.
Claim 10 recites generating the medical imaging data in the machine-readable format by parsing medical imaging data, wherein the medical imaging data comprises a set of variable fields and a set of constant fields, wherein the set of constant fields comprises at least one of text data and binary data corresponding to a patient, an imaging system, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician, and wherein the set of variable fields comprises at least one of text data and binary data corresponding to an examination parameter, a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, one or more examination rules and constraints, and additional examination data; validating the medical imaging data based on the plurality of predefined standards; upon successful validation, encoding the medical imaging data using an encryption technique to generate the encoded medical imaging data; and transmitting the encoded medical imaging data to the receiver. These limitations fall within the scope of the abstract idea as set out above.
Claim 10 recites the additional elements of a) the processor executing instructions to perform the subsequent functions and b) the receiver being a receiver system.
As cited above, paragraphs 17 and 23 describe source system 100 and receiver system 200, while paragraphs 35 and 36 state that source system 100 and receiver system 200 “may be implemented in programmable hardware devices such as programmable gate arrays, programmable array logic, programmable logic devices, or the like” or “implemented in software for execution by various types of processors” such as ASICs. Paragraphs 35 and 36 also describe the instructions as stored in memory devices and accessed by the processor.
Additionally, paragraphs 61-63 state that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer” such as desktops, laptops, mobile phones, or other general-purpose computers, and describe the computer system as employing microprocessors and various types of RAM, ROM, flash memory, and other memory types.
The receiver system and processor are each therefore construed as encompassing generic forms of computer processing and memory devices.
The above elements only amount to mere instructions to implement the functions of the abstract idea using computing elements as tools. Specifically, the receiver system and processor are each only recited at a high level of generality as used to perform functions such as parsing and receiving the medical image data and are disclosed as encompassing generic computing elements. These elements are therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claim 11 recites validating the reconstruction data based on a plurality of predefined clinical rules and the set of constant fields; and generating a reconstructed image based on the validated reconstruction data, wherein the reconstructed image comprises information associated with the source system and the receiver system. These limitations fall within the scope of the abstract idea as set out above.
Examiner notes that the source system and receiver system are not recited in the above limitations as performing any function, and are only recited as being associated with information comprised in the reconstructed image.
Claim 11 recites the additional element of the processor executing instructions to perform the subsequent functions.
As cited above, paragraphs 17 and 23 describe source system 100 and receiver system 200, while paragraphs 35 and 36 state that source system 100 and receiver system 200 “may be implemented in programmable hardware devices such as programmable gate arrays, programmable array logic, programmable logic devices, or the like” or “implemented in software for execution by various types of processors” such as ASICs. Paragraphs 35 and 36 also describe the instructions as stored in memory devices and accessed by the processor.
Additionally, paragraphs 61-63 state that “[t]he disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer” such as desktops, laptops, mobile phones, or other general-purpose computers, and describe the computer system as employing microprocessors and various types of RAM, ROM, flash memory, and other memory types. The processor is therefore construed as encompassing generic forms of computer processing devices.
The above element only amounts to mere instructions to implement the functions of the abstract idea using computing elements as tools. Specifically, the processor is only recited at a high level of generality as used to perform the subsequently recited data analysis functions such as generation and validation of reconstruction data and is disclosed as encompassing generic computing elements. This element is therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claims 1-11 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 9 are indefinite because Examiner is unable to determine the metes and bounds of the respective claims based on the recitation of storing the medical imaging data “based on one or more configurations of the receiver system.” Specifically, it is not clear based on the context of the claims what is being described by “configurations of the receiver system” or what the metes and bounds of such configurations would be. While the specification uses the terminology “receiver system configurations” (see e.g. paragraph 27 of the specification as originally filed) it does not further describe or provide examples of such receiver system configurations. It is therefore not clear what subject matter is encompassed by “configurations of the receiver system.” It is therefore not clear what would fall within the scope of storing the medical imaging data specifically “based on one or more configurations of the receiver system” given that the claim is not merely reciting storing the imaging data, and it is unclear what types of information are being used to modify the storage of the imaging data.
Claims 2-8, 10, and 11 inherit the deficiencies of claims 1 and 9 through dependency and are likewise rejected.
Claim 8 is indefinite because Examiner is unable to determine the metes and bounds of the respective claims based on the recitation of “determining compatibility of the decoded medical imaging data with the receiver system configurations.” Specifically, and as set out above, it is not clear based on the context of the claims what is being described by “receiver system configurations” or what the metes and bounds of such configurations would be. While the specification uses the terminology “receiver system configurations” (see e.g. paragraph 27 of the specification as originally filed) it does not further describe or provide examples of such receiver system configurations. Given that the metes and bounds of the “receiver system configurations” are unclear, it is also unclear what functionality is encompassed by determining compatibility of the medical imaging data with such receiver system configurations.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 2, 5, and 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al (US Patent Application Publication 2024/0013893) in view of Gazelle X Validator Rule Editor (hereinafter Gazelle), VanNostrand (US Patent Application Publication 2007/0143342), Gendron et al (US Patent Application Publication 2002/0023172), and Omernick et al (US Patent Application Publication 2012/0002853).
With respect to claim 1, Choudhury discloses the claimed method of transmitting medical imaging data from a source system to a receiver system, the method comprising:
receiving, by the receiver system, encoded medical imaging data from the source system, wherein the encoded medical imaging data comprises the medical imaging data in a machine-readable format (Figures 1 and 9, [24], [25], [28], [33], [39], and [60] describe DPU 115 receiving encrypted medical image data in a format that does not conform to a medical image data protocol or in a format which does conform to the medical image data protocol);
decoding, by the receiver system, the encoded medical imaging data using a decryption technique (Figure 2, [25], [32], and [33] describe the DPU 115 decrypting the medical data);
mapping, by the receiver system, the decoded medical imaging data based on one or more business objects associated with the receiver system (Figure 9, [25], [37], [41], [43], and [44] describe converting the decrypted data from the format that does not conform to the medical imaging protocol to a first format which does conform to the medical imaging protocol);
storing, by the receiver system, the decoded medical imaging data in a data store associated with the receiver system based on one or more configurations of the receiver system (Figures 1, 4, and 5, [39], [41], and [43] describe storing the data based on rules configured at the receiving system);
but does not expressly disclose:
the received data having been validated based on a plurality of predefined standards;
validating, by the receiver system, the decoded medical imaging data based on the plurality of predefined standards;
mapping the imaging data upon successful validation; and
generating, by the receiver system, reconstruction data based on the stored decoded medical imaging data and an input received from a user, wherein the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image.
However, Gazelle teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to validate converted medical image data based on a plurality of predefined standards (Page 2 ¶1, page 7 ¶1, page 9 ¶3, and page 18 Illustration 21 describes a DICOM system which converts DICOM files into XML and validates the XML files).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the system of Choudhury to validate converted medical image data based on a plurality of predefined standards as taught by Gazelle since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case Choudhury already discloses converting DICOM files into other predefined standards, and validating the files after conversion as taught by Gazelle would perform that same function in Choudhury, making the results predictable to one of ordinary skill in the art (MPEP 2143).
VanNostrand further teaches that it was old and well known in the art of medical image transfer before the effective filing date of the claimed invention to map, by a receiver system, imaging data which has been validated by the receiver system based on the plurality of predefined standards (Figures 1, 3A, 3B, 5, 7, and 8, [19]-[21], [30], [32], and [35] describe a receiver system validating medical imaging data based on predefined standards such as XML and mapping the result to a standard equivalent based on receiver capabilities).
Therefore it would have been obvious to one of ordinary skill in the art of medical image transfer before the effective filing date of the claimed invention to modify the system of Choudhury to map imaging data which has been validated, by a receiver system, based on the plurality of predefined standards as taught by VanNostrand since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case Choudhury already discloses the receiver system receiving medical imaging data in a plurality of predefined standards and mapping the imaging data, and validating the received imaging data based on the standards and mapping the validated data as taught by VanNostrand would perform that same function in Choudhury, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Gendron further teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on stored medical imaging data and an input received from a user (Figure 5, [74], [75], [77], [78], and [81]-[84] describe retrieving and translating particular DICOM imaging data, i.e. generating reconstruction data, based on stored study data and the inputted request from a user).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, and VanNostrand to generate reconstruction data based on stored medical imaging data and an input received from a user and validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, and VanNostrand already teaches storing DICOM files for display (see e.g. Choudhury [26]), and generating reconstruction data based on the stored data and a user input followed by validating the reconstruction data based on predefined clinical rules and constant fields as taught by Gendron would perform that same function in Choudhury, Gazelle, and VanNostrand, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Omernick lastly teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on an orientation parameter of an image received from a user (Figure 3, [17], and [42]-[44] describe a user entering a value for image orientation which is then used to generate the reconstructed image based on the orientation).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, and Gendron to generate reconstruction data based on an orientation parameter of an image received from a user as taught by Omernick since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, and Gendron already teaches generating reconstruction data based on the stored data and a user input, and having the user input include image orientation as taught by Omernick would perform that same function in Choudhury, Gazelle, VanNostrand, and Gendron, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 2, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 1. Choudhury further discloses:
generating, by the source system, the medical imaging data in the machine-readable format by parsing medical imaging data, wherein the medical imaging data comprises a set of variable fields and a set of constant fields (Figure 8, [24], [31], [41], [42], [55], and [56] describe the system parsing medical imaging data of a first format and generating converted data in a second format prior to transmission, where the converted data includes a plurality of types of pixel and header data such as type of modality, study description, series description, and image type);
encoding, by the source system, the medical imaging data using an encryption technique to generate the encoded medical imaging data (Figure 2, [24], [28], [30], and [56] describe the system encrypting the data prior to transmission); and
transmitting, by the source system, the encoded medical imaging data to the receiver system (Figure 2, [28], [34], and [42] describe transmitting the encrypted imaging data from the source system to the receiver system);
but does not expressly disclose:
validating, by the source system, the medical imaging data based on the plurality of predefined standards.
However, Gazelle teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to validate converted medical image data based on a plurality of predefined standards (Page 2 ¶1, page 7 ¶1, page 9 ¶3, and page 18 Illustration 21 describes a DICOM system which converts DICOM files into XML and validates the XML files).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to validate converted medical image data based on a plurality of predefined standards as taught by Gazelle since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already discloses converting DICOM files into other predefined standards prior to transmission, and validating the files after that conversion as taught by Gazelle would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 5, Choudhury/Gazelle/VanNostrand teach the method of claim 1. Choudhury does not expressly disclose validating, by the receiver system, the reconstruction data based on a plurality of predefined clinical rules and the set of constant fields.
However, Gendron teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields (Figures 3 and 4, [61], [64]-[66], [151], and [152] describe the system validating the data based on the associated DICOM information and rules).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches storing DICOM files for display (see e.g. Choudhury [26]), and generating reconstruction data based on the stored data and a user input followed by validating the reconstruction data based on predefined clinical rules and constant fields as taught by Gendron would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Omernick further teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on an orientation parameter of an image received from a user (Figure 3, [17], and [42]-[44] describe a user entering a value for image orientation which is then used to generate the reconstructed image based on the orientation).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to generate reconstruction data based on an orientation parameter of an image received from a user as taught by Omernick since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches generating reconstruction data based on the stored data and a user input, and having the user input include image orientation as taught by Omernick would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 7, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 5. Choudhury does not expressly disclose rendering an error with a reason of failure to the user, for each failed validation corresponding to the medical imaging data, the decoded medical imaging data, and the reconstruction data.
However, Gendron teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to render an error with a reason of failure to a user for failed validations (Figures 11, 12, and 18, [151], [152], [154], and [155] describe the system validating imaging tags and providing reasons for any failures to a user).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to render an error with a reason of failure to a user for failed validations as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches performing validations corresponding to the medical imaging data, the decoded medical imaging data, and the reconstruction data, and rendering an error with a reason of failure to a user for any failed validations as taught by Gendron would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 8, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 1. Choudhury does not expressly disclose wherein storing the decoded medical imaging data comprises determining compatibility of the decoded medical imaging data with the receiver system configurations.
However, VanNostrand teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to determine compatibility of medical imaging data with receiver system configurations as part of storing medical imaging data ([20]-[23], [29], [31], and [34] describe determining portions of received medial imaging data based on the capabilities of the receiving system and sending compatible data to a data storage system).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to determine compatibility of medical imaging data with receiver system configurations as part of storing medical imaging data as taught by VanNostrand since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already discloses a receiving system decoding and storing received medical imaging data, and storing the medical imaging data by determining compatibility of the medical imaging data with receiver system configurations as taught by VanNostrand would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 9, Choudhury discloses the claimed system for transmitting medical imaging data from a source system to a receiver system, the system comprising:
a processor ([63]-[65] describe the system comprising processors); and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions ([63], [68], and [75] describe memory storing instructions executed by the processors), which, on execution, cause the processor to:
receive encoded medical imaging data from the source system, wherein the encoded medical imaging data comprises the medical imaging data in a machine-readable format (Figures 1 and 9, [24], [25], [28], [33], [39], and [60] describe DPU 115 receiving encrypted medical image data in a format that does not conform to a medical image data protocol or in a format which does conform to the medical image data protocol);
decode the encoded medical imaging data using a decryption technique (Figure 2, [25], [32], and [33] describe the DPU 115 decrypting the medical data);
map the decoded medical imaging data based on one or more business objects associated with the receiver system (Figure 9, [25], [37], [41], [43], and [44] describe converting the decrypted data from the format that does not conform to the medical imaging protocol to a first format which does conform to the medical imaging protocol); and
store the decoded medical imaging data in a data store associated with the receiver system based on one or more configurations of the receiver system (Figures 1, 4, and 5, [39], [41], and [43] describe storing the data based on rules configured at the receiving system);
but does not expressly disclose:
the received data having been validated based on a plurality of predefined standards;
validating, by the receiver system, the decoded medical imaging data based on the plurality of predefined standards;
mapping the imaging data upon successful validation; and
generating reconstruction data based on the stored decoded medical imaging data and an input received from a user, wherein the input comprises values corresponding to at least one of a size parameter and an orientation parameter of an image.
However, Gazelle teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to validate converted medical image data based on a plurality of predefined standards (Page 2 ¶1, page 7 ¶1, page 9 ¶3, and page 18 Illustration 21 describes a DICOM system which converts DICOM files into XML and validates the XML files).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the system of Choudhury to validate converted medical image data based on a plurality of predefined standards as taught by Gazelle since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case Choudhury already discloses converting DICOM files into other predefined standards, and validating the files after conversion as taught by Gazelle would perform that same function in Choudhury, making the results predictable to one of ordinary skill in the art (MPEP 2143).
VanNostrand further teaches that it was old and well known in the art of medical image transfer before the effective filing date of the claimed invention to validate, by a receiver system, medical imaging data based on the plurality of predefined standards and subsequently map the imaging data (Figures 1, 3A, 3B, 5, 7, and 8, [19]-[21], [30], [32], and [35] describe a receiver system validating medical imaging data based on predefined standards such as XML and mapping the result to a standard equivalent based on receiver capabilities).
Therefore it would have been obvious to one of ordinary skill in the art of medical image transfer before the effective filing date of the claimed invention to modify the system of Choudhury to validate, by a receiver system, medical imaging data based on the plurality of predefined standards and subsequently map the imaging data as taught by VanNostrand since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case Choudhury already discloses the receiver system receiving medical imaging data in a plurality of predefined standards and mapping the imaging data, and validating the received imaging data based on the standards and mapping the validated data as taught by VanNostrand would perform that same function in Choudhury, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Gendron further teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on stored medical imaging data and an input received from a user (Figure 5, [74], [75], [77], [78], and [81]-[84] describe retrieving and translating particular DICOM imaging data, i.e. generating reconstruction data, based on stored study data and the inputted request from a user).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, and VanNostrand to generate reconstruction data based on stored medical imaging data and an input received from a user and validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, and VanNostrand already teaches storing DICOM files for display (see e.g. Choudhury [26]), and generating reconstruction data based on the stored data and a user input followed by validating the reconstruction data based on predefined clinical rules and constant fields as taught by Gendron would perform that same function in Choudhury, Gazelle, and VanNostrand, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Omernick lastly teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on an orientation parameter of an image received from a user (Figure 3, [17], and [42]-[44] describe a user entering a value for image orientation which is then used to generate the reconstructed image based on the orientation).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, and Gendron to generate reconstruction data based on an orientation parameter of an image received from a user as taught by Omernick since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, and Gendron already teaches generating reconstruction data based on the stored data and a user input, and having the user input include image orientation as taught by Omernick would perform that same function in Choudhury, Gazelle, VanNostrand, and Gendron, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Claims 3, 4, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al (US Patent Application Publication 2024/0013893) in view of Gazelle X Validator Rule Editor (hereinafter Gazelle), VanNostrand (US Patent Application Publication 2007/0143342), Gendron et al (US Patent Application Publication 2002/0023172), and Omernick et al (US Patent Application Publication 2012/0002853) as applied to claims 2 and 9, and further in view of NEMA, DICOM PS3.6 2022d Registry of DICOM Data Elements (hereinafter DICOM Data Elements).
With respect to claim 3, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 2. Choudhury further discloses:
wherein the set of constant fields comprises at least one of text data and binary data corresponding to an imaging system ([41] describes the header data as including the imaging system used to acquire the images; [43] further describes the fields as including binary data fields);
but does not expressly disclose:
the set of constant fields corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician.
However, DICOM Data Elements teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to include a set of constant fields corresponding to a patient (Page 15 lists the DICOM tags including fields such as the patient’s name, ID, birth date, and other information), an institution where the source system is installed (Pages 3 and 9 list the DICOM tags as including the name and address of the institution as well as the relevant department within the institution), cardiac data (Page 40 lists the DICOM tags as including high and low R-R interval values as well as heart rate), pulmonary data (Pages 60, 84, and 85 list the DICOM tags as including information on respiratory cycle position as well as starting and ending respiratory amplitude and phase), injector data (Pages 35, 38, 43 list the DICOM tags as including injector data such as contrast administration route, contrast start/stop time, and syringe counts), a prescribed medicine (Pages 213, 249, and 258 list the DICOM tags as including prescription notes, dose, and sequence), and a certified technician (Pages 9 and 171 list the DICOM tags as including the operator’s name and content creator’s name).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to have a set of constant fields corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician as taught by DICOM Data Elements since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches the set of constant fields including DICOM header tags (see e.g. Choudhury [41] listing the StudyDescription 0008, SeriesDescription 0008, and other 0008 group tags), and having the set of constant fields include DICOM header tags corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician as taught by DICOM Data Elements would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 4, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 2. Choudhury further discloses:
wherein the set of variable fields comprises at least one of text data and binary data corresponding to an examination parameter and additional examination data ([41] describes the variable fields as including the Study Description and Series Description DICOM header tags; [43] further describes the fields as including binary data fields);
but does not expressly disclose:
the set of variable fields corresponding to a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints.
However, DICOM Data Elements teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to include a set of variable fields corresponding to a scan preference (Pages 49, 97, and 98 list the DICOM tags as including depth of scan field, scan pattern type, and scan cycle time/scan rate parameters), an image acquisition parameter (Pages 1, 2, 15, and 42 list the DICOM tags as including acquisition UID, acquisition date, acquisition contrast, and acquisition mode), a bolus tracking detail (Pages 34, 35, and 38 list the DICOM tags as including bolus agent, sequence, reflexivity, administration route, volume, start/stop time, and other information), collimation data (Pages 42 and 47 list the DICOM tags as including collimator grid, type, shape, and other information), a scan geometry (Pages 58, 63, 70, 74, and 81 list the DICOM tags as including geometry sequence, detector geometry, and image geometry type), scan coordinates (Pages 23, 88, 96, and 130 list the DICOM tags as including scan coordinate system data, reference coordinates, X and Y coordinates, and image center point coordinates), and one or more examination rules and constraints (Pages 126, 193, and 194 list the DICOM tags as including scheduled procedure step sequence, constraint type, and constraint violations).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to have a set of variable fields corresponding to a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints as taught by DICOM Data Elements since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches the set of constant fields including DICOM header tags (see e.g. Choudhury [41] listing the StudyDescription 0008, SeriesDescription 0008, and other 0008 group tags), and having the set of variable fields include DICOM header tags corresponding to scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints as taught by DICOM Data Elements would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
With respect to claim 10, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the system of claim 9. Choudhury further discloses wherein the processor-executable instructions further cause the processor to:
generate the medical imaging data in the machine-readable format by parsing medical imaging data, wherein the medical imaging data comprises a set of variable fields and a set of constant fields (Figure 8, [24], [31], [41], [42], [55], and [56] describe the system parsing medical imaging data of a first format and generating converted data in a second format prior to transmission, where the converted data includes a plurality of types of pixel and header data such as type of modality, study description, series description, and image type),
wherein the set of constant fields comprises at least one of text data and binary data corresponding to an imaging system ([41] describes the header data as including the imaging system used to acquire the images; [43] further describes the fields as including binary data fields), and
wherein the set of variable fields comprises at least one of text data and binary data corresponding to an examination parameter and additional examination data ([41] describes the variable fields as including the Study Description and Series Description DICOM header tags; [43] further describes the fields as including binary data fields);
encode the medical imaging data using an encryption technique to generate the encoded medical imaging data (Figure 2, [24], [28], [30], and [56] describe the system encrypting the data prior to transmission); and
transmit the encoded medical imaging data to the receiver system (Figure 2, [28], [34], and [42] describe transmitting the encrypted imaging data from the source system to the receiver system);
but does not expressly disclose:
the set of constant fields corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician;
the set of variable fields corresponding to a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints
validating the medical imaging data based on the plurality of predefined standards.
However, DICOM Data Elements teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to include a set of constant fields corresponding to a patient (Page 15 lists the DICOM tags including fields such as the patient’s name, ID, birth date, and other information), an institution where the source system is installed (Pages 3 and 9 list the DICOM tags as including the name and address of the institution as well as the relevant department within the institution), cardiac data (Page 40 lists the DICOM tags as including high and low R-R interval values as well as heart rate), pulmonary data (Pages 60, 84, and 85 list the DICOM tags as including information on respiratory cycle position as well as starting and ending respiratory amplitude and phase), injector data (Pages 35, 38, 43 list the DICOM tags as including injector data such as contrast administration route, contrast start/stop time, and syringe counts), a prescribed medicine (Pages 213, 249, and 258 list the DICOM tags as including prescription notes, dose, and sequence), and a certified technician (Pages 9 and 171 list the DICOM tags as including the operator’s name and content creator’s name), and a set of variable fields corresponding to a scan preference (Pages 49, 97, and 98 list the DICOM tags as including depth of scan field, scan pattern type, and scan cycle time/scan rate parameters), an image acquisition parameter (Pages 1, 2, 15, and 42 list the DICOM tags as including acquisition UID, acquisition date, acquisition contrast, and acquisition mode), a bolus tracking detail (Pages 34, 35, and 38 list the DICOM tags as including bolus agent, sequence, reflexivity, administration route, volume, start/stop time, and other information), collimation data (Pages 42 and 47 list the DICOM tags as including collimator grid, type, shape, and other information), a scan geometry (Pages 58, 63, 70, 74, and 81 list the DICOM tags as including geometry sequence, detector geometry, and image geometry type), scan coordinates (Pages 23, 88, 96, and 130 list the DICOM tags as including scan coordinate system data, reference coordinates, X and Y coordinates, and image center point coordinates), and one or more examination rules and constraints (Pages 126, 193, and 194 list the DICOM tags as including scheduled procedure step sequence, constraint type, and constraint violations)
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to have a set of constant fields corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician, and a set of variable fields corresponding to a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints as taught by DICOM Data Elements since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches the set of constant fields including DICOM header tags (see e.g. Choudhury [41] listing the StudyDescription 0008, SeriesDescription 0008, and other 0008 group tags), and having the set of constant fields include DICOM header tags corresponding to a patient, an institution where the source system is installed, cardiac data, pulmonary data, injector data, a prescribed medicine, and a certified technician, and a set of variable fields corresponding to a scan preference, an image acquisition parameter, a bolus tracking detail, collimation data, a scan geometry, scan coordinates, and one or more examination rules and constraints as taught by DICOM Data Elements would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Gazelle lastly teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to validate converted medical image data based on a plurality of predefined standards (Page 2 ¶1, page 7 ¶1, page 9 ¶3, and page 18 Illustration 21 describes a DICOM system which converts DICOM files into XML and validates the XML files).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to validate converted medical image data based on a plurality of predefined standards as taught by Gazelle since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already discloses converting DICOM files into other predefined standards prior to transmission, and validating the files after that conversion as taught by Gazelle would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al (US Patent Application Publication 2024/0013893) in view of Gazelle X Validator Rule Editor (hereinafter Gazelle), VanNostrand (US Patent Application Publication 2007/0143342), Gendron et al (US Patent Application Publication 2002/0023172) and Omernick et al (US Patent Application Publication 2012/0002853) as applied to claim 5, and further in view of Kotula et al (US Patent Application Publication 2010/0211409).
With respect to claim 6, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the method of claim 5. Choudhury does not expressly disclose generating a reconstructed image based on the validated reconstruction data, wherein the reconstructed image comprises information associated with the source system and the receiver system.
However, Gendron teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate a reconstructed image based on validated reconstruction data (Figure 2 element 26, [26], [28], [74], and [86] describe generating a reconstructed image based on the validated data for viewing by a clinician).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to generate a reconstructed image based on validated reconstruction data as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches generating reconstruction data and validating the data, and generating a reconstructed image based on the validated data as taught by Gendron would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Kotula further teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate a reconstructed image comprising information associated with a source system and a receiver system (Figures 1A, 2, and 3, [14], [26], [49], [56], [63], and [68] show and describe a system receiving medical images, using image metadata to generate manifest information, and then generating reconstructed images having information associated with the transmitting facility such as the facility’s name and imaging modality, as well as information from the manifest file).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to generate a reconstructed image comprising information associated with a source system and a receiver system as taught by Kotula since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches a source system and receiving system as well as generating a reconstructed image, and generating a reconstructed image comprising information associated with a source system and a receiver system as taught by Kotula would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al (US Patent Application Publication 2024/0013893) in view of Gazelle X Validator Rule Editor (hereinafter Gazelle), VanNostrand (US Patent Application Publication 2007/0143342), Gendron et al (US Patent Application Publication 2002/0023172), and Omernick et al (US Patent Application Publication 2012/0002853) as applied to claim 9, and further in view of Kotula et al (US Patent Application Publication 2010/0211409).
With respect to claim 11, Choudhury/Gazelle/VanNostrand/Gendron/Omernick teach the system of claim 9. Choudhury does not expressly disclose wherein the processor-executable instructions further cause the processor to: validate the reconstruction data based on a plurality of predefined clinical rules and the set of constant fields; and generate a reconstructed image based on the validated reconstruction data, wherein the reconstructed image comprises information associated with the source system and the receiver system.
However, Gendron teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to (Figure 5, [74], [75], [77], [78], and [81]-[84] describe retrieving and translating particular DICOM imaging data, i.e. generating reconstruction data, based on stored study data and the inputted request from a user), validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields (Figures 3 and 4, [61], [64]-[66], [151], and [152] describe the system validating the data based on the associated DICOM information and rules), and generate a reconstructed image based on validated reconstruction data (Figure 2 element 26, [26], [28], [74], and [86] describe generating a reconstructed image based on the validated data for viewing by a clinician)
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to validate the reconstruction data based on a plurality of predefined clinical rules and set of constant fields, and generate a reconstructed image based on validated reconstruction data as taught by Gendron since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches storing DICOM files for display (see e.g. Choudhury [26]), and generating reconstruction data based on the stored data and a user input followed by validating the reconstruction data based on predefined clinical rules and constant fields and generating the reconstruction image as taught by Gendron would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Omernick further teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate reconstruction data based on an orientation parameter of an image received from a user (Figure 3, [17], and [42]-[44] describe a user entering a value for image orientation which is then used to generate the reconstructed image based on the orientation).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to generate reconstruction data based on an orientation parameter of an image received from a user as taught by Omernick since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches generating reconstruction data based on the stored data and a user input, and having the user input include image orientation as taught by Omernick would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Kotula lastly teaches that it was old and well known in the art of medical image processing before the effective filing date of the claimed invention to generate a reconstructed image comprising information associated with a source system and a receiver system (Figures 1A, 2, and 3, [14], [26], [49], [56], [63], and [68] show and describe a system receiving medical images, using image metadata to generate manifest information, and then generating reconstructed images having information associated with the transmitting facility such as the facility’s name and imaging modality, as well as information from the manifest file).
Therefore it would have been obvious to one of ordinary skill in the art of medical image processing before the effective filing date of the claimed invention to modify the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick to generate a reconstructed image comprising information associated with a source system and a receiver system as taught by Kotula since the claimed invention is only a combination of these old and well known elements which would have performed the same function in combination as each did separately. In the present case the combination of Choudhury, Gazelle, VanNostrand, Gendron, and Omernick already teaches a source system and receiving system as well as generating a reconstructed image, and generating a reconstructed image comprising information associated with a source system and a receiver system as taught by Kotula would perform that same function in Choudhury, Gazelle, VanNostrand, Gendron, and Omernick, making the results predictable to one of ordinary skill in the art (MPEP 2143).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Koutelakis et al, PACS through Web Compatible with DICOM Standard and WADO Service: Advantages and Implementation;
Yu et al, XML-Based DICOM Data Format;
Zhang et al, Implementation methods of medical image sharing for collaborative health care based on IHE XDS-I profile;
Silva et al, A community-driven validation service for standard medical imaging objects;
Hu et al (US Patent Application Publication 2010/0246981);
Oliveres (US Patent Application Publication 2023/0162837);
Westin et al (US Patent Application Publication 2019/0335096);
Liu et al (WO 2011/051103);
Kibble et al (US Patent Application Publication 2020/0312440).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Gregory Lultschik/Examiner, Art Unit 3682