DETAILED ACTION
This is responsive to RCE filed on 12/24/2025 in which claims 1 and 3 -9 are presented for examination; Claims 1 and 7 have been amended. Claim 2 has been canceled.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/24/2025 has been entered.
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, and 3-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1:
Step 1: Is the claim to a process, machine, manufacture or composition of matter?” Yes, it’s a machine(apparatus).
Step 2a Prong 1 (judicial exception)
Step 2A (1): “Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes , the claim comes under mental processes.
Claim 1 recites:
“.A medical information processing system comprising : a medical diagnostic imaging apparatus including processing circuitry; a first database; a second database including a first library and a second library; and a third database including a predetermined library, wherein the processing circuitry configured to: receive from the first database, examination information a case and an examination body part of a subject; acquire a first search result including multiple imaging protocol candidates by searching the first library using the case of the subject as a first search key, the first library associating an imaging protocol with each case; acquire a second search result by searching the second library using the examination body part of the subject as a second search key, the second library associating a slice condition with each examination body part ; display a selection menu including the multiple imaging protocol candidates; determine a particular imaging protocol for the subject in response to selection by an operator of one imaging protocol candidate on the displayed selection menu; determine a particular slice condition for the subject based on the second search result; and store the received examination information of the subject and the determined imaging protocol and the determined slice condition in the predetermined library in such a manner as to associate them with each other.”
All the limitations above are abstract idea related to the mental process (concepts performed in the human mind (including an observation, evaluation, judgment, opinion)) with the exception of bold and underlined limitations. Claim language pertains to receiving examination information(e.g. a medical report) including all the clinical information and specific body part needed to be examined. Information regarding the patient’s case and specific body part(e.g., slice condition) can be easily looked up from the medical examination report provided. All this information can be written on the paper. For example, see Fig. 6 of the instant specification. Using such table on a paper one can search and find all the corresponding information. Any information regarding to patient can be stored using pen and paper and can be looked up/searched as needed.
Step 2A(2): Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. NO
The claim does recite additional elements; however they don’t integrate the exception into a practical application of the exception.
medical information processing system (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
medical diagnostic imaging apparatus (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
processing circuitry(Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
database(Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
library(Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
receive from the first database(Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g) )
store the received examination information (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g) )
display(Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: evaluate whether the claim recites additional elements that amount to an inventive concept (aka “significantly more”) than the recited judicial exception? NO
As discussed previously with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
Regarding the claim limitations:
receive from the first database(the courts have recognized the computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (“i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information”); See, MPEP 2106.05 (d)(II)
store the received examination information (iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; See, MPEP 2106.05 (d)(II)
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Dependent claims 3- 6 and 8-9 , further narrows the abstract idea and add the additional elements of “display”, “imaging device” .
Under step 2A, prong two, the additional elements don’t integrate the exception into a practical application of the exception as merely adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
As discussed previously with respect to Step 2A Prong Two, the additional elements in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Regarding claim 7, it is a method claim and rejected under the same rationale as claim 1.
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 and 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over GOTO et al. ( US 20170319166 A1) in view of Palmer et al. (US 20220076804 A1)
Regarding claim 1, GOTO teaches a medical diagnostic information processing system comprising:
a medical diagnostic imaging apparatus including processing circuitry(see Fig. 3);
wherein the processing circuitry is configured to:
receive [from the first database] examination information including a case and an examination body part of a subject (para, “[0136] For example, the updating function 37d extracts keywords from the history shown in FIG. 20 per imaging plan. Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information. Note: here case is “Colorectal cancer” and body part is “large intestine” (See, Fig. 19));
acquire a first search result including multiple imaging protocol candidates by searching [the first library] using the case of the subject as a first search key, [the first library] associating an imaging protocol with each case ( para “[0139] For example, the updating function 37d extracts “colorectal cancer” as a keyword that is included in an examination order with high frequency. The updating function 37d then searches for a history that includes the extracted keyword “colorectal cancer” in the examination order. When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.”);
Also, para, “[0136] For example, the updating function 37d extracts keywords from the history shown in FIG. 20 per imaging plan. Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information.” Note: here imaging plan “detailed examination of colorectal cancer” is the imaging protocol that is associated with case “Colorectal cancer.”)
acquire a second search result by searching the [second library] using the examination body part of the subject as a second search key, [the second library] associating a slice condition with each examination body part (para ,“[0082] As shown in FIG. 10, for example, the storage 35 stores information in which an imaging plan “detailed examination of lung area”, an imaging part “lung”, a scan start position “1 cm above flag point (landmark) at upper end of right lung”, and a scan end position “1 cm below flag point at lower end of left lung” are associated with each other. This information indicates that the imaging part in the imaging plan named “detailed examination of lung area” is a lung, and an area from 1 cm above a flag point (landmark) at an upper end of a right lung to 1 cm below a flag point at a lower end of a left lung is the scan area. Moreover, the storage 35 stores information about a scan range of other imaging plans similarly.” Note: here slice condition is scan start and end position (See, Fig. 10, 19) ; also see para 0118);
display a selection menu including the multiple imaging protocol candidates( para, “[0140] When multiple imaging plans are presented as candidates, the X-ray CT apparatus 1 can present them by assigning priority orders. In this case, for example, the X-ray CT apparatus 1 can present sequentially from an imaging plan included in histories with high frequency, or can present sequentially from an imaging plan with a latest date of record in histories.” Note: here, presenting is displaying. Also, para 0137 “.... According to this arrangement, the operator can select a desired imaging plan without searching for the desired imaging plan from multiple imaging plans...”
Also, para, “[0139] ...When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.”)
determine a particular imaging protocol for the subject in response to selection by an operator of one imaging protocol candidate on the displayed selection menu (para, “[0139] For example, the updating function 37d extracts “colorectal cancer” as a keyword that is included in an examination order with high frequency. The updating function 37d then searches for a history that includes the extracted keyword “colorectal cancer” in the examination order. When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.” Note: here imaging plan is determined i.e. "detailed examination of colorectal cancer" is the imaging protocol that is associated with case "Colorectal cancer.
Also, para “[0136].... Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information.");
determine a particular slice condition for the subject based on the second search result (para, “[0118] Although a case of improving the reproducibility relating to a scan range has been explained in the above embodiment, embodiments are not limited thereto. For example, for a reconstruction range also, a history of operation indicating that a range is changed can be learned and reflected in next imaging and after, similarly. That is, the imaging condition that can be learned by the X-ray CT apparatus 1 is an imaging condition that is defined by at least one position of a part. Moreover, for example, an imaging condition such as a slice thickness can be learned also.” Note: Also, para 0143 for scan range.);
and store the received examination information of the subject and the determined imaging protocol and the determined slice condition in the predetermined library in such a manner as to associate them with each other(para, “[0081] FIG. 10 shows one example of information of a scan range per imaging plan that is stored in the storage 35 according to the first embodiment. As shown in FIG. 10, the storage 35 stores information in which an imaging plan, an imaging part, a scan start position, and a scan end position are associated with each other. Among these, the imaging plan is a list of imaging plans that have been registered in the X-ray CT apparatus 1. Moreover, the imaging part is information indicating a part of a subject, such as a lung, a large intestine, and a head, to be a subject of imaging in an imaging plan. Furthermore, the scan start position indicates a position at which scan is started, and the scan end position indicates a position at which the scan is ended. That is, a range between the scan start position and the scan end position corresponds to a scan range. The information about a scan range stored in the storage 35 is, for example, registered in advance by an operator.” Note: Also, see Fig. 10 below.
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GOTO does not explicitly teach:
a first database;
a second database including a first library and a second library;
and a third database including a predetermined library,
receive from the first database [examination information including a case and an examination body part of a subject];
[acquire a first search result by searching] the first library [using the case of the subject as a first search key], the first library [associating an imaging protocol with each case]
[acquire a second search result by searching] the second library, [using the examination body part of the subject as a second search key,] the second library [associating a slice condition with each examination body part]
Palmer teaches:
a first database (para , “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”)
a second database including a first library and a second library( para, “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”
Fig. 3A shows plurality of libraries; note data libraries are just datasets that are stored in the database.);
and a third database including a predetermined library (para, “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”
Fig. 3A shows plurality of libraries; note data libraries are just datasets that are stored in the database.
Para, “[0080] FIGS. 3A-3D (collectively, “FIG. 3”) are schematic diagrams illustrating various non-limiting examples 300, 300′, 300″, and 300′″ of image data library metadata that may be used when implementing an imaging discovery utility for augmenting clinical image management, in accordance with various embodiments.” Note: here image data library is a predetermined library for image data.);
receive from the first database [examination information including a case and an examination body part of a subject](para, “[0050] Herein, structured query language (“SQL”) might refer to a standard language that is used for handling relational databases, which define relationships in the form of tables…”
Also, para “[0024] The solution implements the coupling of a structured and unstructured database. The structured database may contain the minimum required data fields to make the image discoverable or searchable, while the unstructured database may provide the capability to dynamically enhance or enrich data fields based on user needs or as more information is derived from the image. The data structure also links artifacts to the image, such artifacts including, but not limited to, image processing analysis files, segmentation files, three-dimensional (“3D”) print files, machine learning (“ML”) algorithm files, and/or the like. Searches may be performed across the data fields as well as across the associated files and artifacts….”)
[acquire a first search result by searching] the first library [using the case of the subject as a first search key], the first library [associating an imaging protocol with each case] (para, “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”
Fig. 3A shows plurality of libraries; note data libraries are just datasets that are stored in the database.);
[acquire a second search result by searching] the second library, [using the examination body part of the subject as a second search key,] the second library [associating a slice condition with each examination body part]( para “[0050] Herein, structured query language (“SQL”) might refer to a standard language that is used for handling relational databases, which define relationships in the form of tables…” Note: Fig. 10 (GOTO) already teaches table with such relationship, and Palmer teaches that SQL can be used to search such table.)
It would have been obvious for a person of ordinary skill in the art to apply relational database teachings of Palmer into the teachings of GOTO at the time the application was filed in order to perform search across the data table fields. (para 0024, “Searches may be performed across the data fields as well as across the associated files and artifacts. An additional feature of the system is the ability to aggregate images into sets or collections based on search criteria.”)
Regarding claim 7, GOTO teaches a medical information processing method for a medical information processing system comprising
a medical diagnostic imaging apparatus, [a first database, a second database including a first library and a second library, and a third database including a predetermined library,] wherein the method comprises( see Fig. 3) :
receiving [from the first database ] examination information including a case and an examination body part of a subject(para, “[0136] For example, the updating function 37d extracts keywords from the history shown in FIG. 20 per imaging plan. Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information. Note: here case is “Colorectal cancer” and body part is “large intestine” (See, Fig. 19));
acquiring a first search result including multiple imaging protocol candidates by searching [the first library] using the case of the subject as a first search key, [the first library] associating an imaging protocol with each case( para, “para “[0139] For example, the updating function 37d extracts “colorectal cancer” as a keyword that is included in an examination order with high frequency. The updating function 37d then searches for a history that includes the extracted keyword “colorectal cancer” in the examination order. When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.”);
Also, para “[0136] For example, the updating function 37d extracts keywords from the history shown in FIG. 20 per imaging plan. Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information.” Note: here imaging plan “detailed examination of colorectal cancer” is the imaging protocol that is associated with case “Colorectal cancer.”);
acquiring a second search result by searching the [second library] using the examination body part of the subject as a second search key, [the second library] associating a slice condition with each examination body part (para ,“[0082] As shown in FIG. 10, for example, the storage 35 stores information in which an imaging plan “detailed examination of lung area”, an imaging part “lung”, a scan start position “1 cm above flag point (landmark) at upper end of right lung”, and a scan end position “1 cm below flag point at lower end of left lung” are associated with each other. This information indicates that the imaging part in the imaging plan named “detailed examination of lung area” is a lung, and an area from 1 cm above a flag point (landmark) at an upper end of a right lung to 1 cm below a flag point at a lower end of a left lung is the scan area. Moreover, the storage 35 stores information about a scan range of other imaging plans similarly.”) Note: here slice condition is scan start and end position (See, Fig. 10, 19) ; also see para 01118);
displaying a selection menu including the multiple imaging protocol candidates(para, “[0140] When multiple imaging plans are presented as candidates, the X-ray CT apparatus 1 can present them by assigning priority orders. In this case, for example, the X-ray CT apparatus 1 can present sequentially from an imaging plan included in histories with high frequency, or can present sequentially from an imaging plan with a latest date of record in histories.” Note: here, presenting is displaying. Also, para 0137 “.... According to this arrangement, the operator can select a desired imaging plan without searching for the desired imaging plan from multiple imaging plans...”
Also, para, “[0139] ...When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.”);
determining a particular imaging protocol for the subject in response to selection by an operator of one imaging protocol candidate on the displayed selection menu( (para, “[0139] For example, the updating function 37d extracts “colorectal cancer” as a keyword that is included in an examination order with high frequency. The updating function 37d then searches for a history that includes the extracted keyword “colorectal cancer” in the examination order. When imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” are extracted by this search, for example, the updating function 37d associates the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” with the keyword “colorectal cancer”. Thus, for example, when the keyword “colorectal cancer” is extracted from a received examination order, the X-ray CT apparatus 1 presents the two imaging plans “detailed examination of colorectal cancer” and “simple imaging of colorectal cancer” as candidates of an imaging plan, to an operator.” Note: here imaging plan is determined i.e. "detailed examination of colorectal cancer" is the imaging protocol that is associated with case "Colorectal cancer.
Also, para “[0136].... Three histories of the dates “4/3 14:25”, “4/5 12:21”, and “4/5 17:05” are all histories of the imaging plan “detailed examination of colorectal cancer”. The updating function 37d extracts a common keyword from the examination order of the three histories. In this case, “colorectal cancer” is extracted as a common keyword from the three histories. Therefore, if the keyword “colorectal cancer” is included in an examination order, the updating function 37d associates the keyword “colorectal cancer” and the imaging plan “detailed examination of colorectal cancer” to records/updates this information.");
determining a particular slice condition for the subject based on the second search result(para, “[0118] Although a case of improving the reproducibility relating to a scan range has been explained in the above embodiment, embodiments are not limited thereto. For example, for a reconstruction range also, a history of operation indicating that a range is changed can be learned and reflected in next imaging and after, similarly. That is, the imaging condition that can be learned by the X-ray CT apparatus 1 is an imaging condition that is defined by at least one position of a part. Moreover, for example, an imaging condition such as a slice thickness can be learned also.” Note: Also, para 0143 for scan range);
and storing the received examination information of the subject and the determined imaging protocol and the determined slice condition in the predetermined library in such a manner as to associate them with each other(para, “[0081] FIG. 10 shows one example of information of a scan range per imaging plan that is stored in the storage 35 according to the first embodiment. As shown in FIG. 10, the storage 35 stores information in which an imaging plan, an imaging part, a scan start position, and a scan end position are associated with each other. Among these, the imaging plan is a list of imaging plans that have been registered in the X-ray CT apparatus 1. Moreover, the imaging part is information indicating a part of a subject, such as a lung, a large intestine, and a head, to be a subject of imaging in an imaging plan. Furthermore, the scan start position indicates a position at which scan is started, and the scan end position indicates a position at which the scan is ended. That is, a range between the scan start position and the scan end position corresponds to a scan range. The information about a scan range stored in the storage 35 is, for example, registered in advance by an operator.” Note: Also, see Fig. 10 below.
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GOTO does not explicitly teach:
[a medical diagnostic imaging apparatus], a first database, a second database including a first library and a second library, and a third database including a predetermined library, [wherein the method comprises]
receiving from the first database [examination information including a case and an examination body part of a subject]
[ a first search result by searching] the first library [using the case of the subject as a first search key,] the first library [associating an imaging protocol with each case]
[acquiring a second search result by searching] the second library [using the examination body part of the subject as a second search key], the second [library associating a slice condition with each examination body part]
Palmer teaches:
[a medical diagnostic imaging apparatus], a first database, a second database including a first library and a second library, and a third database including a predetermined library, [wherein the method comprises] (para , “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”
Fig. 3A shows plurality of libraries; note data libraries are just datasets that are stored in the database.;
Para, “[0080] FIGS. 3A-3D (collectively, “FIG. 3”) are schematic diagrams illustrating various non-limiting examples 300, 300′, 300″, and 300′″ of image data library metadata that may be used when implementing an imaging discovery utility for augmenting clinical image management, in accordance with various embodiments.” Note: here image data library is a predetermined library for image data.)
receiving from the first database [examination information including a case and an examination body part of a subject] ](para, “[0050] Herein, structured query language (“SQL”) might refer to a standard language that is used for handling relational databases, which define relationships in the form of tables…”
Also, para “[0024] The solution implements the coupling of a structured and unstructured database. The structured database may contain the minimum required data fields to make the image discoverable or searchable, while the unstructured database may provide the capability to dynamically enhance or enrich data fields based on user needs or as more information is derived from the image. The data structure also links artifacts to the image, such artifacts including, but not limited to, image processing analysis files, segmentation files, three-dimensional (“3D”) print files, machine learning (“ML”) algorithm files, and/or the like. Searches may be performed across the data fields as well as across the associated files and artifacts….”)
[ a first search result by searching] the first library [using the case of the subject as a first search key,] the first library [associating an imaging protocol with each case](para , “[0148] In certain embodiments, the system can include one or more databases 720a-720n (collectively, “databases 720”)….”
Fig. 3A shows plurality of libraries; note data libraries are just datasets that are stored in the database.);
[acquiring a second search result by searching] the second library [using the examination body part of the subject as a second search key], the second [library associating a slice condition with each examination body part] ]( para “[0050] Herein, structured query language (“SQL”) might refer to a standard language that is used for handling relational databases, which define relationships in the form of tables…” Note: Fig. 10 (GOTO) already teaches table with such relationship, and Palmer teaches that SQL can be used to search such table.)
It would have been obvious for a person of ordinary skill in the art to apply relational database teachings of Palmer into the teachings of GOTO at the time the application was filed in order to perform search across the data table fields. (para 0024, “Searches may be performed across the data fields as well as across the associated files and artifacts. An additional feature of the system is the ability to aggregate images into sets or collections based on search criteria.”)
Regarding claim 8 GOTO as modified by Palmer teaches the system of claim 1.
GOTO further teaches wherein the medical diagnostic imaging apparatus is at least one of an X-ray apparatus, an X-ray Computed Tomography (CT) apparatus, a Positron-Emission Tomography (PET) apparatus, a magnetic resonance (MR) apparatus, an ultrasound apparatus, or a single-photon emission computed tomography (SPECT) apparatus(para, “[0095] FIG. 16 and FIG. 17 are flowcharts showing a processing procedure by the X-ray CT apparatus 1 according to the first embodiment. In FIG. 16, processing when a history if an operation is stored by the storing function 37c in an examination is explained, and in FIG. 17, processing when a scan range is updated by the updating function 37d is explained.”)
Regarding claim 9 GOTO as modified by Palmer teaches the system of claim 1.
GOTO further teaches further comprising
an imaging device configured to scan the subject(para, “[0048] The scan control circuitry 33 controls collection processing of projection data in the base 10 by controlling operation of the X-ray-irradiation control circuit 11, the base driving circuit 16, the data collecting circuit 14, and the bed driving device 21, under control of the processing circuitry 37. Specifically, the scan control circuitry 33 controls positioning imaging to collect a positioning image (scano-image), and collection processing of projection data in actual imaging (actual scanning) to collect an image to be used for diagnosis. The X-ray CT apparatus 1 according to the first embodiment can image a two-dimensional scano-image and a three-dimensional scano-image.”),
wherein the processing circuitry is further configured to acquire a medical image of the subject by controlling the imaging device to scan the subject based on the determined imaging protocol and the determined slice condition(para, “[0028] Moreover, in the medical-information processing system 100, for example, a hospital information system (HIS), a radiology information system (RIS), or the like is installed, and various kinds of information is managed. For example, the terminal device 3 transmits an examination order that is created according to the system described above to the X-ray CT apparatus 1 or the server device 2. The X-ray CT apparatus 1 acquires patient information from the examination order directly received from the terminal device 3, or from a patient list (modality work list) per modality created by the server device 2 that has received the examination order, and collects X-ray CT-image data per patient. The X-ray CT apparatus 1 transmits the collected X-ray CT-image data or image data that is generated by performing various kinds of image processing on the X-ray CT-image data, to the server device 2. The server device 2 stores the X-ray CT-image data and the image data that are received from the X-ray CT apparatus 1, generates image data from X-ray CT-image data, and transmits, to the terminal device 3, image data according to an acquisition request from the terminal device 3. The terminal device 3 displays the image data received from the server device 2 on a monitor and the like. In the following, the respective devices are explained.
Also, para “[0075] The position comparing function 37b can convert a scan range that is specified on the virtual patient image into a scan range on the positioning image, by the acquired coordinate transformation matrix “H”. For example, the position comparing function 37b can convert a scan range “SRV” specified on the virtual patient image into a scan range “SRC” on the positioning image as shown in FIG. 8, by using the coordinate transformation matrix “H”. FIG. 9 shows a conversion example of a scan range by coordinate transformation according to the first embodiment. For example, as shown on the virtual patient image in FIG. 9, when an operator sets the scan range “SRV” on the virtual patient image, the position comparing function 37b converts the set scan range “SRV” into the scan range “SRC” on the scano-image by using the coordinate transformation matrix described above.”),
and display the acquired medical image(“para,[0028] ….. The server device 2 stores the X-ray CT-image data and the image data that are received from the X-ray CT apparatus 1, generates image data from X-ray CT-image data, and transmits, to the terminal device 3, image data according to an acquisition request from the terminal device 3. The terminal device 3 displays the image data received from the server device 2 on a monitor and the like. In the following, the respective devices are explained.”)
Claims 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over GOTO as modified by Palmer and in view of Hsieh et al. (US 20230056923 A1)
Regarding claim 3, GOTO as modified by Palmer teaches the system according to claim 1.
GOTO as modified by Palmer doesn’t explicitly teach wherein the processing circuitry is further configured to:
acquire a third search result by searching a third library using the case of the subject as a third search key, the third library associating post-processing with each case;
determine a particular post-processing for the subject based on the third search result;
and store the received examination information of the subject and the determined post-processing in the predetermined library in such a manner as to associate them with each other.
Hsieh teaches wherein the processing circuitry is configured to:
acquire a third search result by searching a third library using the case of the subject as a third search key, the third library associating post-processing with each case (para, “[0083] The post-processing component 228 can also select and apply one or more post-processing tasks for processing the medical image series based on the one or more automatically detected scan series characteristics. …… The post-processing component 228 can automatically invoke and apply the appropriate image processing models for a series based on the specific scan characteristics automatically detected by the series characterization models. For example, in an implementation in which a series characterization model includes an artifact detection model that detected presence of an artifact in the one or more representative images, the post-processing component 228 can automatically select and apply an artifact reduction/correction image processing model on one or more of the original images in the series to remove/correct artifacts included therein. Further, the artifact reduction/correction image processing models can be tailored to specific types of anatomies and/or specific types of artifacts. In this regard, the post-processing component 228 can select and apply the appropriate artifact reduction/correction image processing model based on the detected series type, anatomy present, and the specific type of artifact detected.” Note: here, based on artifact (patient case such as type of implant), the post processing can be determined. ; also, as mentioned in response to argument, number of libraries or database is merely duplication of parts, so if we can have first and second library, we can also have 100th library.
Also, para “[0082] ….In particular, the similar case study component 226 can accesses a medical image database comprising a plurality of different medical image studies (e.g., medical image database 206), identify a subset (e.g., one or more) of the different medical images studies that are similar to the medical image series based on the one or more characteristics, and extract the subset for performance of comparative analysis between the subset and the medical image series. For example, the similar cases can be presented to a radiologist (or another reviewing entity) via the visualization application in association with reviewing the current medical image series. In another example, the similar cases can be aggregated and used for additional post-processing tasks and applications (e.g., model training, receiving expert review, used for continued learning and reporting, etc.). In some implementation, the similar case study component 226 can also be configured to find and pull similar medical image exams (e.g., series) for the same patient for the purpose of performing longitudinal studies. In this regard, the similar case study component 226 can employ an identifier for the patient associated with the current medical image series and find and pull (e.g., extract) other cases for the same patient identifier that were performed in the past and have one or more of the same or similar series characteristics (e.g., same series type, same contrast phase, etc.).”)
determine a particular post-processing for the subject based on the third search result (para, “[0083] The post-processing component 228 can also select and apply one or more post-processing tasks for processing the medical image series based on the one or more automatically detected scan series characteristics. …… The post-processing component 228 can automatically invoke and apply the appropriate image processing models for a series based on the specific scan characteristics automatically detected by the series characterization models. For example, in an implementation in which a series characterization model includes an artifact detection model that detected presence of an artifact in the one or more representative images, the post-processing component 228 can automatically select and apply an artifact reduction/correction image processing model on one or more of the original images in the series to remove/correct artifacts included therein. Further, the artifact reduction/correction image processing models can be tailored to specific types of anatomies and/or specific types of artifacts. In this regard, the post-processing component 228 can select and apply the appropriate artifact reduction/correction image processing model based on the detected series type, anatomy present, and the specific type of artifact detected.” Note: here, based on artifact (patient case such as type of implant), the post processing can be determined.);
and store the received examination information of the subject and the determined post-processing in the predetermined library in such a manner as to associate them with each other (para,” [0025] The automatically detected scan characteristics can also be used to automatically invoke the appropriate post-processing applications. For example, automated algorithms and analysis can be run for each series without needing the clinician to manually invoke them. For instance, in one example use-case for an automated cardiac exam, the exam type detection can determine which series is the most appropriate for calcium scoring analysis and which is for the coronary analysis. The analysis steps for each can be automatically invoked and reports generated. Similarly knowing the content of each series, even specific heart chamber segmentation algorithms or other image processing algorithms (e.g., organ segmentation, fat segmentation, lesion detection/scoring, and the like) can be invoked automatically and added to the report.” Note: here, the most appropriate post processing can be determined automatically, thus system have stored association that can be used to find most appropriate post-processing applications.)
It would have been obvious for a person of ordinary skill in the art to apply determining post-processing teachings of Hsieh into the teachings of GOTO as modified by Palmer at the time the application was filed in order to determine applicable post-processing tasks. (Para, “[0078] The scan series characteristics data 106 can further be employed to automatically invoke applicable post-processing tasks, image analysis task, and reporting tasks as well as optimize the visualization workflows.”)
Regarding claim 4, GOTO as modified by Palmer and Hsieh teaches the system according to claim 3.
GOTO further teaches further comprising an imaging device configured to perform a scan of the subject, wherein the processing circuitry is further configured to acquire a medical image of the subject by controlling the imaging device to perform the scan based on the determined imaging protocol, the determined slice condition, and the determined post-processing(para, “[0028] Moreover, in the medical-information processing system 100, for example, a hospital information system (HIS), a radiology information system (RIS), or the like is installed, and various kinds of information is managed. For example, the terminal device 3 transmits an examination order that is created according to the system described above to the X-ray CT apparatus 1 or the server device 2. The X-ray CT apparatus 1 acquires patient information from the examination order directly received from the terminal device 3, or from a patient list (modality work list) per modality created by the server device 2 that has received the examination order, and collects X-ray CT-image data per patient. The X-ray CT apparatus 1 transmits the collected X-ray CT-image data or image data that is generated by performing various kinds of image processing on the X-ray CT-image data, to the server device 2. The server device 2 stores the X-ray CT-image data and the image data that are received from the X-ray CT apparatus 1, generates image data from X-ray CT-image data, and transmits, to the terminal device 3, image data according to an acquisition request from the terminal device 3. The terminal device 3 displays the image data received from the server device 2 on a monitor and the like. In the following, the respective devices are explained.
Also, para “[0075] The position comparing function 37b can convert a scan range that is specified on the virtual patient image into a scan range on the positioning image, by the acquired coordinate transformation matrix “H”. For example, the position comparing function 37b can convert a scan range “SRV” specified on the virtual patient image into a scan range “SRC” on the positioning image as shown in FIG. 8, by using the coordinate transformation matrix “H”. FIG. 9 shows a conversion example of a scan range by coordinate transformation according to the first embodiment. For example, as shown on the virtual patient image in FIG. 9, when an operator sets the scan range “SRV” on the virtual patient image, the position comparing function 37b converts the set scan range “SRV” into the scan range “SRC” on the scano-image by using the coordinate transformation matrix described above.”).
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over GOTO as modified by Palmer and in view of Igarashi (US 20120278359 A1)
Regarding claim 5, GOTO as modified by Palmer teaches the medical diagnostic imaging apparatus according to claim 1.
GOTO further teaches wherein the processing circuitry is further configured to:
receive personal information including at least one of a gender, an age group, a weight, a presence or an absence of an allergy, a pulse, or a cardiorespiratory function of the subject (para, “[0070] First, the virtual patient image is explained. The virtual patient images are created in advance as images that have been obtained by actually radiographing human bodies that have a standard physique according to respective combinations of parameters relating to body size such as age, adult/infant, male/female, weight, and height, and is stored in the storage 35. That is, the storage 35 stores data of multiple virtual patient images according to combinations of parameters described above. With the virtual patient image stored in the storage 35, an anatomical landmark (landmark) is associated to be stored. For example, in a human body, there are many anatomical landmarks that can be extracted relatively easily from an image based on the structural characteristics and the like by image processing such as pattern recognition. The positions and arrangements of these many anatomical landmarks in a body are roughly determined according to the age, adult/infant, male/female, the weight, the height, and the like.” Also note, the secondary reference also teaches personal information as claimed.);
GOTO as modified by Palmer doesn’t explicitly teach:
acquire a fourth search result by searching a fourth library using the personal information and the examination information of the subject as a fourth search key,
the fourth library associating an imaging protocol and a slice condition with each piece of personal information and each piece of examination information;
and determine the particular imaging protocol and the particular slice condition for the subject based on the fourth search result.
Igarashi teaches:
acquire a fourth search result by searching a fourth library that associates an imaging protocol and a slice condition with each piece of personal information and each piece of examination information using the personal information and the examination information of the subject as a fourth search key (para, “[0032] The patient information acquisition unit 5 has a function to acquire patient information included in examination order information for each patient and study when the examination order information has been supplied to the image diagnostic apparatus 1 from the medical information management system 3 through the network 2. The patient information acquired in the patient information acquisition unit 5 includes patient-specific information such as a name, an ID, a height, a weight, a sex, a date of birth and an age of a patient. Further, desired information, included in examination order information, such as information specifying an imaging part can be added to the patient information acquired by the patient information acquisition unit 5 as incidental information.”
Also, para, “[0040] Note that, when no examination information of a patient specified by patient information is stored in the medical image server 4, past examination information of a patient having equivalent characteristics such as a body shape, a sex and an age may be acquired from the medical image server 4 by the examination information acquisition unit 6.” Also, See Fig.3.),
the fourth library associating an imaging protocol and a slice condition with each piece of personal information and each piece of examination information( para, [0017] According to another embodiment, a medical image server includes a database and a database controlling unit. The database is configured to store medical image data. The database controlling unit is configured to search the database based on patient information managed in a medical information management system to acquire past examination information corresponding to the patient information to transmit the acquired past examination information to an image diagnostic apparatus when a request for transmitting the past examination information corresponding to the patient information was transmitted from the image diagnostic apparatus.
[0018] According to another embodiment, an image diagnostic method includes searching a medical image server based on patient information to acquire past examination information corresponding to the patient information automatically from the medical image server when the patient information was supplied from a medical information management system; and performing imaging according to an imaging condition set by referring to the examination information.” Note: Also, see Fig. 3; also, as mentioned in response to argument, number of libraries or database is merely duplication of parts, so if we can have first and second library, we can also have 100th library)
and determine the particular imaging protocol and the particular slice condition for the subject based on the fourth search result (para, “[0034] The examination information acquisition unit 6 has a function to automatically transmit request of transmission of past examination information corresponding to patient information and search conditions of the examination information to the medical image server 4 through the network 2 when the patient information acquisition unit 5 has acquired the patient information and a function to receive and acquire the past examination information when the past examination information has been transmitted from the medical image server 4 as a response to the request of transmission of the past examination information. Therefore, operation of the examination information acquisition unit 6 makes it possible to search the medical image server 4 based on patient information to automatically acquire past examination information corresponding to the patient information, in the image diagnostic apparatus 1 side, from the medical image server 4 when the patient information was supplied from the medical information management system 3 to the image diagnostic apparatus 1.”
Also, para, “[0035] Examination information to be a target of transmission request can be medical image data itself, examination information included in medical image data or examination information, corresponding to medical image data, stored separately from the medical image data. When medical image data is stored as DICOM image data in the medical image server 4, examination information can be acquired from tag information attached to the medical image data.”
Also, “[0037] Therefore, examination information such as imaging conditions corresponding to specific patient information can be acquired from the data areas identified by the standard tag and the private tag of DICOM image data. Meanwhile, medical image data can be acquired as examination information from the data area identified by the image tag.” Para, 0039 teaches imaging part; also note as taught in primary references, all these information are examining information, and instant reference teaches that one can retrieve the examination information using personal information.)
It would have been obvious for a person of ordinary skill in the art to apply personal information teachings of IGARASHI into the teachings of GOTO as modified by Palmer at the time the application was filed in order to acquire examination information based on patient’s personal information. (Abstract, “According to one embodiment, an image diagnostic apparatus includes an examination information acquisition unit and an imaging unit. The examination information acquisition unit searches a medical image server based on patient information to acquire past examination information corresponding to the patient information automatically from the medical image server….)
Regarding claim 6, GOTO as modified by Palmer teaches the system according to claim 1.
GOTO further teaches:
wherein the examination information of the subject further includes an examination posture of the subject (para, “[0049] For example, the scan control circuitry 33 images a two-dimensional scano-image by performing continuous imaging with the X-ray tube 12a fixed at a position of 0 degree (position in a front direction for a subject) while moving the top plate at a constant speed. Alternatively, the scan control circuitry 33 images a two-dimensional scano-image by repeating intermittent imaging synchronized with movement of the top plate, with the X-ray tube 12a fixed at the position of 0 degree, while moving the top plate intermittently. The scan control circuitry 33 can image a positioning image not only from the front direction for the subject, but also from any direction (for example, a side direction, and the like).”
Also,. See Fig. 6, Fig. 9, Fig. 19.),
and the processing circuitry is further configured to: receive personal information including at least one of a gender, an age group, a weight, a presence or an absence of an allergy, a pulse, or a cardiorespiratory function of the subject (para, “[0070] First, the virtual patient image is explained. The virtual patient images are created in advance as images that have been obtained by actually radiographing human bodies that have a standard physique according to respective combinations of parameters relating to body size such as age, adult/infant, male/female, weight, and height, and is stored in the storage 35. That is, the storage 35 stores data of multiple virtual patient images according to combinations of parameters described above. With the virtual patient image stored in the storage 35, an anatomical landmark (landmark) is associated to be stored. For example, in a human body, there are many anatomical landmarks that can be extracted relatively easily from an image based on the structural characteristics and the like by image processing such as pattern recognition. The positions and arrangements of these many anatomical landmarks in a body are roughly determined according to the age, adult/infant, male/female, the weight, the height, and the like.” Also note, the secondary reference also teaches personal information as claimed.);
GOTO as modified by Palmer doesn’t explicitly teach:
acquire a fourth search result by searching a fourth library using the personal information and the examination information of the subject as a fourth search key,
the fourth library associating an imaging protocol and a slice condition with each piece of personal information and each piece of examination information;
and determine the particular imaging protocol and the particular slice condition for the subject based on the fourth search result.
Igarashi teaches:
acquire a fourth search result by searching a fourth library that associates an imaging protocol and a slice condition with each piece of personal information and each piece of examination information using the personal information and the examination information of the subject as a fourth search key (“[0032] The patient information acquisition unit 5 has a function to acquire patient information included in examination order information for each patient and study when the examination order information has been supplied to the image diagnostic apparatus 1 from the medical information management system 3 through the network 2. The patient information acquired in the patient information acquisition unit 5 includes patient-specific information such as a name, an ID, a height, a weight, a sex, a date of birth and an age of a patient. Further, desired information, included in examination order information, such as information specifying an imaging part can be added to the patient information acquired by the patient information acquisition unit 5 as incidental information.”
Also, “[0040] Note that, when no examination information of a patient specified by patient information is stored in the medical image server 4, past examination information of a patient having equivalent characteristics such as a body shape, a sex and an age may be acquired from the medical image server 4 by the examination information acquisition unit 6.” Also, See Fig.3.),
the fourth library associating an imaging protocol and a slice condition with each piece of personal information and each piece of examination information( para, [0017] According to another embodiment, a medical image server includes a database and a database controlling unit. The database is configured to store medical image data. The database controlling unit is configured to search the database based on patient information managed in a medical information management system to acquire past examination information corresponding to the patient information to transmit the acquired past examination information to an image diagnostic apparatus when a request for transmitting the past examination information corresponding to the patient information was transmitted from the image diagnostic apparatus.
[0018] According to another embodiment, an image diagnostic method includes searching a medical image server based on patient information to acquire past examination information corresponding to the patient information automatically from the medical image server when the patient information was supplied from a medical information management system; and performing imaging according to an imaging condition set by referring to the examination information.” Note: Also, see Fig. 3 )
and determine the particular imaging protocol and the particular slice condition for the subject based on the fourth search result (para, “[0034] The examination information acquisition unit 6 has a function to automatically transmit request of transmission of past examination information corresponding to patient information and search conditions of the examination information to the medical image server 4 through the network 2 when the patient information acquisition unit 5 has acquired the patient information and a function to receive and acquire the past examination information when the past examination information has been transmitted from the medical image server 4 as a response to the request of transmission of the past examination information. Therefore, operation of the examination information acquisition unit 6 makes it possible to search the medical image server 4 based on patient information to automatically acquire past examination information corresponding to the patient information, in the image diagnostic apparatus 1 side, from the medical image server 4 when the patient information was supplied from the medical information management system 3 to the image diagnostic apparatus 1.”
Also, “[0035] Examination information to be a target of transmission request can be medical image data itself, examination information included in medical image data or examination information, corresponding to medical image data, stored separately from the medical image data. When medical image data is stored as DICOM image data in the medical image server 4, examination information can be acquired from tag information attached to the medical image data.”
Also, “[0037] Therefore, examination information such as imaging conditions corresponding to specific patient information can be acquired from the data areas identified by the standard tag and the private tag of DICOM image data. Meanwhile, medical image data can be acquired as examination information from the data area identified by the image tag.” Para, 0039 teaches imaging part; also note as taught in primary references, all these information are examining information, and instant reference teaches that one can retrieve the examination information using personal information.)
It would have been obvious for a person of ordinary skill in the art to apply personal information teachings of IGARASHI into the teachings of GOTO as modified by Palmer at the time the application was filed in order to acquire examination information based on patient’s personal information. (Abstract, “According to one embodiment, an image diagnostic apparatus includes an examination information acquisition unit and an imaging unit. The examination information acquisition unit searches a medical image server based on patient information to acquire past examination information corresponding to the patient information automatically from the medical image server….)
Response to Arguments
Applicant's arguments filed on 15 have been fully considered but they are not persuasive.
Remarks - 35 USC § 101
In remarks, Pg. 11-12 , applicant contends:
“ In particular, Applicant respectfully submits that Claim 1 recites a technological
improvement, presenting a technological solution to a technological problem, and thus recites significantly more than any asserted abstract idea. ..................... This leads to the advantage set forth in paragraph 62 " dispersing the pieces of information contained in a conversion database in multiple libraries based on this assumption can reduce the amount of data managed by the medical diagnostic imaging apparatus and reduce the chance of managing duplicate data due to combinations of a case and an examination body part. As a result, the maintenance of the medical diagnostic imaging apparatus 1 is improved. Emphasis added. Moreover, in amended Claim 1, in this example, the second database, and not the medical diagnostic imaging apparatus, includes the first library and the second library. Such a system configuration reduces the amount of data managed by the medical diagnostic imaging apparatus. Thus, amended Claim 1 brings about a technological improvement in the maintenance of the medical diagnostic imaging apparatus. Thus, Claim 1 recites a specific implementation that leads to a specific improvement over prior systems.”
Dispersing pieces of information contained in database/multiple libraries does not bring technical improvement . Any data can be contained in multiple libraries for easy retrieval and management and a simple computer can be used as a tool to perform the task. Duplicate data can also be managed in any database by assigning e.g. unique identifiers/keys , standardizing data etc. Also, reducing the amount of data needed to be managed can also be done using data minimization , compression etc. , and this factor does not bring any technological improvement and does not integrate the invention into practical application. More, importantly, the claims don’t describe any technical detail as how the dispersion of data is being achieved; merely stating that data is being stored in multiple libraries, is nothing more than business decision.
In remarks, Pg.13 , applicant contends:
“In this regard, Applicant notes that the Office Action on page 6, regarding Claim 9, appears to merely disclose that "[t]he additional elements in the claim amounts to no more than mere instructions to apply the exception using a generic computer component." Applicant strongly disagrees. Claim 9 requires that the processing circuitry is configured to acquire a medical image of the subject by controlling the imaging device to scan the subject based on the determined imaging protocol and the determined slice condition, and display the acquired medical image. Claim 9 requires control of another device similar to the claim at issue in the Supreme Court case of Diamond V. Diehr. Applicant respectfully submits that controlling an imaging device to control a subject is not merely applying this exception using a generic computer component, but is control of another device. Applicant strongly traverses the rejection of Claim 9.”.”
The applicant states “Claim 9 requires that the processing circuitry is configured to acquire a medical image of the subject by controlling the imaging device to scan the subject based on the determined imaging protocol and the determined slice condition, and display the acquired medical image”, and provides no explanation as to how this is not merely applying the device, rather provides a conclusory statement. The image diagnosing/scanning tools available in healthcare (MRI, CT, X-ray) visualize internal body structures and document scanners (Epson, Ricoh) that digitize patient records and identification at the point of care. Furthermore, instant specification, para 0021 makes it clear that generic tools are being used to perform the claimed limitation:
“ [0021] The medical diagnostic imaging apparatus 1 is an apparatus that acquires a medical image for diagnosis of a patient. The medical diagnostic imaging apparatus 1 is, for example, an endoscope apparatus, a plain X-ray imaging apparatus, an X-ray computed tomography (CT) apparatus, a single photon emission computed tomography (SPECT) apparatus, a positron-emission tomography (PET) apparatus, a diagnostic magnetic resonance (MR) apparatus, a diagnostic ultrasonic (UL) apparatus, and an apparatus that combines these apparatuses (e.g., a SPECT-CT apparatus, a PET-CT apparatus). Hereinafter, a “patient” is an example of a subject. That is, each process according to the embodiment is also applicable to a subject other than a patient.”
Regarding, Diamond V. Diehr, MPEP 2106.05 (e) states:
“Diamond v. Diehr provides an example of a claim that recited meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment. 450 U.S. 175, 209 USPQ 1 (1981). In Diehr, the claim was directed to the use of the Arrhenius equation (an abstract idea or law of nature) in an automated process for operating a rubber-molding press. 450 U.S. at 177-78, 209 USPQ at 4. The Court evaluated additional elements such as the steps of installing rubber in a press, closing the mold, constantly measuring the temperature in the mold, and automatically opening the press at the proper time, and found them to be meaningful because they sufficiently limited the use of the mathematical equation to the practical application of molding rubber products. 450 U.S. at 184, 187, 209 USPQ at 7, 8. In contrast, the claims in Alice Corp. v. CLS Bank International did not meaningfully limit the abstract idea of mitigating settlement risk. 573 U.S. 208, 110 USPQ2d 1976 (2014). In particular, the Court concluded that the additional elements such as the data processing system and communications controllers recited in the system claims did not meaningfully limit the abstract idea because they merely linked the use of the abstract idea to a particular technological environment (i.e., "implementation via computers") or were well-understood, routine, conventional activity recited at a high level of generality. 573 U.S. at 225-26, 110 USPQ2d at 1984-85.”
The citation, actually supports examiner’s position that "the additional elements such as the data processing system and communications controllers recited in the system claims did not meaningfully limit the abstract idea because they merely linked the use of the abstract idea to a particular technological environment.”
In remarks, Pg.13 , applicant contends:
“Moreover, whether or not an element is generic or not cannot be considered in the practical application analysis. See the Revised Guidance which states that "Examiners should note however, that Revised Step 2A specifically excludes consideration of whether the additional elements represent well-understood, routine. conventional activity Accordingly. in Revised Step 2A Examiners should ensure that they give weight to all additional elements, whether or not they are conventional, when evaluating whether a judicial exception has been integrated into a practical application.' However, Applicant respectfully submits that the Office clearly does not follow the Revised Guidance in its analysis of Claim 9, and asserts that Claim 9 involves a generic computer component, which is improper and inaccurate.”
MPEP 2106.04(d) recites:
“The courts have also identified limitations that did not integrate a judicial exception into a practical application:[AltContent: rect]
Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); [AltContent: rect]
Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and [AltContent: rect]
Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).”
Note: As can be seen, courts have found that limitations that merely use a computer as a tool to perform an abstract idea (generic computing device) don’t integrate the judicial exception into practical application.
Remarks - 35 USC § 103
In remarks, Pg. 8-9 , applicant contends:
“However, as admitted by the Office Action, the '166 application fails to disclose at least the first, second, and third databases including the first library, the second library, and the predetermined library recited in amended Claim 1.”
The claim is rejected under obviousness i.e. USC 103, and the secondary reference is introduced to provide the explicit teaching for argued limitation.
In remarks, Pg. 9-10 , applicant contends:
“Moreover, Applicant respectfully submits that the '166 application fails to disclose processing circuitry configured to display a selection menu including the multiple imaging protocol candidates; and determine a particular imaging protocol for the subject in response to selection by an operator of one imaging protocol candidate on the displayed selection menu, as recited in amended Claim 1. Rather, the '166 application merely discloses presenting multiple imaging plan candidates, and enables presenting sequentially from an imaging plan included in histories with high frequency or presenting sequentially from an imaging plan with a latest data of record in histories. See '166 paragraph 140. In particular, Applicant respectfully submits that the '166 application is completely silent regarding a second library associating a slice condition with each examination body part, as required by amended Claim 1.”
The amended language has been addressed above in office action. For the limitation, regarding “second library associating a slice condition with each examination body part,”
GOTO para (“[0067] For example, the detecting function 37a extracts a region R1 corresponding to “lung” in the volume data as shown in FIG. 6 based on the information of positional relationship indicating “lung apex: 2 centimeters (cm) to 3 cm above clavicle”, “lower end of lung” height of the seventh rib”, and the like, and on the coordinate information of the respective part. That is, the detecting function 37a extracts coordinate information of voxels of the region R1 in the volume data. The detecting function 37a accompanies the extracted coordinate information to the volume data, associating with the part information to store it. Similarly, the detecting function 37a can extract a region R2 corresponding to “heart” in the volume data as shown in FIG. 6.” Also, see Fig. 11 , para 0085, 0086. The library is discussed in secondary reference (Palmer to complement the primary reference and to teach explicit teaching). The references can’t be looked in vacuum, the primary reference as stated above teaches association between slice condition with each examination body part, similar to Fig. 3B of instant specification (See, GOT, Fig. 10). The only aspect not being disclosed here is that element that is providing this association is not called a second library; however, examiner have introduced Palmer reference that explicitly teaches:
“[0081] With reference to FIG. 3, the various image data library metadata might be embodied as spreadsheet data containing metadata tags for one or more medical image files, although the image data library metadata is not limited to such and can be embodied as any suitable data structure or in any suitable format or file. In some embodiments, the image data library metadata may include, without limitation, one or more instructions for entering metadata or metadata tags, one or more source library metadata, one or more subject library metadata, one or more scan library metadata, and/or one or more device library metadata, or the like....”
In remarks, Pg. 10 , applicant contends:
“However, Applicant respectfully submits that the '804 application fails to remedy the deficiencies of the '166 application, and appears to merely disclose a database system. Thus, no matter how the teachings of the '166 and '804 applications are combined, the combination does not teach or suggest processing circuitry configured to display a selection menu including the multiple imaging protocol candidates: and determine a particular imaging protocol for the subject in response to selection by an operator of one imaging protocol candidate on the displayed selection menu, as recited in amended Claim 1.”
The amended language has been addressed in the office action above (please see OA above). Also, see response to the previous argument.
Conclusion
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/HUMA WASEEM/Examiner, Art Unit 3686
/JASON B DUNHAM/Supervisory Patent Examiner, Art Unit 3686
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