DETAILED ACTION
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 office action is in response to amendment filed on 09/21/2026.
Limitations appearing inside of {} are intended to indicate the limitations not taught by said prior art(s)/combinations.
Claims 1-20 are pending in the application.
Response to Amendments
The Amendment filled 09/16/2026 in response to Non-Final Office Action mailed 06/23/2026 has been entered. Claims 1, 2, 4-14, and 17-20 have been amended. Objection of drawings has been withdrawn in light of applicant remarks/argument. Rejections under 35 USC §§102 and 103 have been withdrawn in light of amended claims.
Response to Arguments/Remarks
Applicant’s arguments, see Remarks, filed 09/21/2026, with respect to Drawing objections have been fully considered and are persuasive. The objection of 06/23/2026 has been withdrawn.
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 1-10, and 12-19 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over “Sabol” (Sabol, et al., US 20040052328 A1) in view of “Tung” (Tung et al., US 20190139271 A1)
Regarding claim 13, Sabol teaches a provision system for a medical image data set, comprising:
a medical imaging facility (interpretation: medical imaging facility can be or comprise a magnetic resonance facility and/or a computer tomography facility and/or a tomosynthesis facility and/or a PET facility and/or an ultrasound facility (CT system 10; Sabol, Fig 1) configured to acquire raw data in an acquisition process (tomographic data set … may be the raw image acquisition data ; Sabol, ¶[0047]);
a first reconstruction facility (interpretation: “reconstructing a preliminary image data set from the raw data via a first reconstruction facility, wherein reconstruction parameters of a predetermined default parameter set are used” (¶[0014])) (See Sabol Fig 7 exhibits RECONSTRUCTION2-3 processes 125 (i.e., reconstruction facility)); and
an analysis facility (interpretation: “designed to provide computer aided diagnosis (CAD) and/or clinical decision support system (CDSS) and/or computer aided risk scoring (CARS)” (¶[0021])) (CAD processing; Sabol, ¶[0063]; and See Sabol, Fig 7 exhibits SEGMENTATION1-3 75, FEATURE EXTRACTION1-3 78 and CLASSIFICATION1-3 82 (i.e., analysis facility)),
the first reconstruction facility and the analysis facility being connected via a communication link (See Sabol, Fig 7 exhibits reconstruction 125, connected via communication link with segmentation 75, feature extraction 78, and classification 82 (i.e., analysis facility)),
wherein the first reconstruction facility of is configured to reconstruct a preliminary image data set from the raw data (The tomographic data set on which the CAD algorithm is implemented may be the raw image acquisition data ; Sabol, ¶[0047]),
the reconstructing of the preliminary image data set being performed using a first parameter set {of reconstruction parameters, and the first parameter set being a default parameter set} (Sabol teaches acquisition parameter: acquisition parameters 84 may be provided by an operator or in an automated manner which affect the tomographic image date acquisition 72. Such acquisition parameters 84 may affect the set of tomographic data acquired and thereby influence the outcome of the CAD processes employed; Sabol, ¶[0046]),
the analysis facility is configured to analyze the preliminary image data set via an analysis algorithm to determine an item of analysis information that describes image content of the preliminary image data set (The segmentation portion 74 of the CAD algorithm, depicted in greater detail in FIG. 4, may identify a particular region of interest based upon calculated features in all or part of the tomographic data set 88.; Sabol, ¶[0048]),
the first reconstruction facility, a further reconstruction facility or the analysis facility is configured to determine a second parameter set {of reconstruction parameters as a function of the analysis information} (Post-processing 98 may include various combinatorial techniques for coordinating the results of the manual and automated segmentation processes. These combinatorial techniques may include manual adjustment of control points resulting from the automatic segmentation process, such as for threshold adjustment, contour adjustment, and other fine tuning steps; Sabol, ¶[0050]), and
the first reconstruction facility or the further reconstruction facility is configured to determine the medical image data set from at least one of the raw data or the preliminary image data set (acquired projection data 120 may be utilized in the reconstruction processes 125 which reconstruct the slice image data 122 or the image volume data 124 ( i.e., medical image data set); Sabol, ¶[0063]),
the determining the medical image data set being performed using the second parameter set (A segmented data set 98 results from the segmentation process 92, 94 and the optional post-processing process (i.e., second parameter set); Sabol, ¶[0050]; The visualization process 80 of the CAD algorithm permits reconstruction of useful images for review by human or machine observers. Thus, various types of images may be presented to the attending physician or to any other person needing such information, based upon any or all of the processing and modules performed by the CAD algorithm; Sabol ¶[0056]).
Sabol teaches the reconstructing of the preliminary image data set being performed using a first parameter set; Sabol does not explicitly disclose a first parameter set of reconstruction parameters, and the first parameter set being a default parameter set.
Sabol does not explicitly a second parameter set of reconstruction parameters as a function of the analysis information, and the determining the medical image data set being performed using the second [reconstruction] parameter set .
However, Tung, a similar field of endeavor of medical image reconstruction, teaches the reconstructing of the preliminary image data set being performed using a first parameter set of reconstruction parameters, and the first parameter set being a default parameter set (default set of reconstruction parameters, the preview images are generated in the background; Tung, ¶[0041]; step 506, the AI engine 6 recommends a default set of reconstruction parameters; Tung, ¶[0048]; and Generate and display preview images, [Fig 7]; after a first preview image is selected, further preview images are generated; ¶[0038]).
Tung further teaches the first reconstruction facility, a further reconstruction facility or the analysis facility is configured to determine a second parameter set of reconstruction parameters as a function of the analysis information; and the determining the medical image data set being performed using the second parameter set (At a step 508, the AE 12 (“AI engine or anticipatory engine”; ¶[0032]) generates alternate sets of reconstruction parameters. At a step 510, preview images reconstructed with the alternate sets of reconstruction parameters are generated; Tung¶[0048])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include generating reconstruction image sets using default and alternative (i.e., second) reconstruction parameters as taught by Tung to the invention of Sabol. The motivation to do so would be to recommend the parameter settings for image reconstruction techniques to deliver personalized optimal image quality as well as anticipate and adapt to the evolving clinician preferences by proactively recommending reconstruction parameters to improve the workflow efficiency and maximally utilize the computing resources (Tung , ¶[0004]).
Claim 1 is similarly analyzed as analogous claim 13.
Regarding claim 2, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches wherein the raw data includes raw data from a screening examination (The tomographic data set on which the CAD algorithm is implemented may be the raw image acquisition data; Sabol, ¶[0047]).
Regarding claim 3, the combination of Sabol and Tung teaches the method of claim 2. Sabol further teaches wherein the screening examination is a tomosynthesis examination of a female breast (tomosynthesis mammography systems (XR); Sabol, [0027]).
Regarding claim 4, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches wherein the preliminary image dataset includes an overview image data set (interpretation: the overview image data set may be a synthetic 2D image and/or one that corresponds to a predetermined acquisition process (¶[0032])) (the CAD processing may be performed on an acquisition projection data set prior to reconstruction, on two-dimensional reconstructed data (both in axial and scout modes), on three-dimensional reconstructed data (volume data or multiplanar reformats), or a suitable combination of such formats; Sabol ¶[[0045]).
Regarding claim 5, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches wherein at least one of,
the analysis algorithm comprises a trained analysis function;
the analysis algorithm is optimized; or
the analysis algorithm is trained for use on the default parameter set (The training process 76 may be utilized to train the feature normalization process 112 to enhance the classification process based upon prior knowledge and experiences; Sabol, ¶[0059]).
Regarding claim 6, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches wherein the analysis information includes at least one of an annotation or a structured report (The visualization 80 (i.e., reporting) may include two- or three-dimensional renderings, superposition of feature markers, color or intensity variations, and so forth. A superposed marker (i.e., annotation) may convey information, such as a feature classification, a probability associated with a classification, or three-dimensional location information of the feature, without obscuring the reconstructed anatomic data. In addition, while a marker may consist of a displayed pointer or text (i.e., annotation), it may also include a color-coded overlay, a color or intensity variation, or any other addition that is recognized and understood by the operator. Typically, CAD provides the ability to display such markers on any of the multiple data. This allows the reviewer to view only a single data or image upon which the results from an array of CAD operations, such as different levels or types of segmentation, feature extraction or classification processes, may be superimposed. In such cases, the markers may be differentiated, such as by color or shape, to allow the reviewer to determine which operation produced the marker; Sabol, ¶[0057]).
Regarding claim 7, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches wherein the analysis information comprises at least one score or lesion information, the lesion information relating to at least one potential lesion (The visualization 80 may include two- or three-dimensional renderings, superposition of feature markers, color or intensity variations, and so forth. A superposed marker may convey information, such as a feature classification, a probability associated with a classification, or three-dimensional location information of the feature, without obscuring the reconstructed anatomic data; Sabol, ¶[0057]).
Regarding claim 8, the combination of Sabol and Tung teaches the method of claim 1. Tung further teaches wherein the second parameter set providing at least one of a higher dimensionality, a higher resolution, a changed contrast, a contrast enhancement, a changed filtering, a changed binning, a changed denoising, an additional denoising, a changed layering property of layers of a reconstructing result, or a reconstruction of additional image data relative to the default parameter set (each reconstruction route anticipating a change to at least one reconstruction parameter affecting the final reconstruction of scanned patient imaging data, wherein the anticipation is based on optimization, a weighted technician preference, alternate algorithm, and/or alternate filter; Tung, ¶[0008]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include an alternate filter with the second parameter set as taught by Tung to the invention of Sabol. The motivation to do so would be to obtain sharper, smoother reconstructed images with desirable noise characteristics using an optimal filter.
Regarding claim 9, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches further comprising storing the medical image data set in an image archiving facility (the operator workstation 40 may also be coupled to a picture archiving and communications system (PACS) 44. It should be noted that PACS 44 may be coupled to a remote system 46, radiology department information system (RIS), hospital information system (HIS) or to an internal or external network, so that others at different locations may gain access to the image and to the image data[ Sabol, ¶[0035]).
Regarding claim 10, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches further comprising: evaluating, by the analysis facility, the medical image data set using an evaluation algorithm to determine evaluation information that describes the image content (feature diagnosis may also be performed as part of the CAD algorithm by means of an optional feature classification process 82, as depicted in FIG. 3 and in greater detail in FIG. 6 ,Sabol, ¶[0058]).
Regarding claim 12, the combination of Sabol and Tung teaches the method of claim 1. Sabol further teaches further comprising: {archiving an evaluation result (interpretation: evaluation result, for example a diagnosis; specification ¶[0059]) with the medical image data set}, (See Sabol Fig 1, shown below, exhibits computer 36 in which the CAD algorithm performs diagnostics, and exhibits the computer 35 in communication with the operator workstation 40 in communication with PACS, the storage facility. Further, “The visualization process 80 of the CAD algorithm permits reconstruction of useful images for review by human or machine observers; Sabol ¶[0056], is interpreted ) as the reading on the claims, because a person of ordinary skill in the art would understand that the PACs systems in medical imaging is capable of archiving diagnosis with the medical images.
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the evaluation result being determined by evaluating at least one user input from an evaluator (The CAD algorithm may facilitate detection alone or may also facilitate diagnosis. Subsequent processing and data acquisition is, then, entirely at the discretion and based upon the expertise of the practitioner; Sabol, ¶[0044];
Regarding claim 14, the combination of Sabol and Tung teaches the method of claim 13. Sabol further teaches wherein the first reconstruction facility is part of the medical imaging facility (The computer 36 is typically coupled to the system controller 24. The data collected by the data acquisition system 34 may be transmitted to the computer 36 and moreover, to a memory 38. It should be understood that any type of memory to store a large amount of data may be utilized by such an exemplary system 10. Also, the computer 36 is configured to receive commands and scanning parameters from an operator via an operator workstation 40 typically equipped with a keyboard and other input devices. An operator may control the system 10 via the input devices. Thus, the operator may observe the reconstructed image and other data relevant to the system from computer 36, initiate imaging, and so forth.; Sabol, ¶[0034]).
Regarding claim 15, the combination of Sabol and Tung teaches a non-transitory computer program product including instructions which, when executed in a provision system, causes the provision system to perform the method of claim 1 (Code stored on the tangible medium includes a routine for acquiring a tomographic data set from a tomographic mammography system; Sabol, ¶[0014]).
Regarding claim 16, the combination of Sabol and Tung teaches the method of claim 4. Sabol further teaches wherein the overview image data set is two-dimensional (the CAD processing may be performed on an acquisition projection data set prior to reconstruction, on two-dimensional reconstructed data (both in axial and scout modes), on three-dimensional reconstructed data (volume data or multiplanar reformats), or a suitable combination of such formats; Sabol ¶[[0045]).
Regarding claim 17, the combination of Sabol and Tung teaches the method of claim 6. Sabol further teaches wherein the analysis information includes the structured report in a first format (The visualization 80 may include two- or three-dimensional renderings, superposition of feature markers, color or intensity variations, and so forth. A superposed marker may convey information, such as a feature classification, a probability associated with a classification, or three-dimensional location information of the feature, without obscuring the reconstructed anatomic data. In addition, while a marker may consist of a displayed pointer or text, it may also include a color-coded overlay, a color or intensity variation, or any other addition that is recognized and understood by the operator. Typically, CAD provides the ability to display such markers on any of the multiple data. This allows the reviewer to view only a single data or image upon which the results from an array of CAD operations, such as different levels or types of segmentation, feature extraction or classification processes, may be superimposed. In such cases, the markers may be differentiated, such as by color or shape, to allow the reviewer to determine which operation produced the marker; Sabol, [0057]).
Regarding claim 18, the combination of Sabol and Tung teaches the method of claim 8. Sabol further teaches wherein the medical image dataset includes additional data relative to the preliminary image data set (The feature identification process 100 may also process the patient data 99 for information related to patient history, such as age, smoking, family history, pregnancy history, weight, BIRAD classification, genetic or proteomic profile, hormonal status, etc., for factors which may weight aspects of the feature identification process 100, such as by adjusting threshold values or weighting factors; Sabol, ¶[0052]).
Regarding claim 19, the combination of Sabol and Tung teaches the method of claim 9. Sabol further teaches wherein the storing includes storing the medical image data set in the image archiving facility for retrieval from a diagnostic facility of an evaluator (operator workstation 40 may also be coupled to a picture archiving and communications system (PACS) 44. It should be noted that PACS 44 may be coupled to a remote system 46, radiology department information system (RIS), hospital information system (HIS) or to an internal or external network, so that others at different locations may gain access to the image and to the image data; ¶[0035]).
Claims 11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sabol in view of Tung, and further in view of “Chen” (Chen et al., US 10734116 B2).
Regarding claim 11, the combination of Sabol and Tung teaches the method of claim 1. Sabol does not explicitly disclose further comprising: specifying at least one of a processing target or a task to be carried out using DICOM.
However, Chen, a similar field of endeavor of systems that store, share, render, simulate and/or facilitate imaging of medical procedures for purposes of optimized performance, simulation, training and/or accreditation, teaches wherein at least one of a further processing target or a task to be carried out is carried out using DICOM (wherein the at least one first 2D medical image computer data file comprises, is decoded from, or is generated from, a DICOM-format medical image file; Chen, [Col 11:1-4]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include DICOM image as taught by Chen to the combined invention of Sabol and Tung. The motivation to do so would be to utilize a common format of medical imaging. DICOM is a standard for handling, storing, printing, and transmitting information in medical imaging (Chen; [Col 9:1-15]).
Regarding claim 20, the combination of Sabol and Tung teaches the method of claim 1. Sabol does not explicitly disclose wherein at least the first reconstruction facility and the analysis facility are configured as DICOM clients.
However, Chen teaches wherein at least the first reconstruction facility and the analysis facility are designed as DICOM clients (according to the present invention, 2D/3D/4D medical image data can be viewed or edited without the need for special hardware and/or system. In other words, browsers would now have the capabilities to decode 2D/3D/4D medical image formats (e.g. DICOM images); Chen, [Col 9:48-52]; The workstation will be configured as a DICOM node inside the local area network; Chen, [Col 62:51-52]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yaqub et al., (Yaqub M, Jinchao F, Arshid K, Ahmed S, Zhang W, Nawaz MZ, Mahmood T. Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities. Comput Math Methods Med. 2022 Jun 16;2022:8750648. doi: 10.1155/2022/8750648. PMID: 35756423; PMCID: PMC9225884.) teaches an overview of deep learning techniques of image reconstruction.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHANDHANA PEDAPATI whose telephone number is (571)272-5325. The examiner can normally be reached M-F 8:30am-6pm (ET).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chan Park can be reached at 5712727409. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHANDHANA PEDAPATI/Examiner, Art Unit 2669 /CHAN S PARK/Supervisory Patent Examiner, Art Unit 2669
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