DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
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 of this title, 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, 8 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks.
As per Claim 1, Chen teaches a computer-implemented method for assessing an image-generating procedure of magnetic resonance imaging,
wherein in the image-generating procedure, an image recording procedure using at least one accelerating technique is combined with a reconstruction procedure including a reconstruction function trained using machine learning, (Chen, Paragraph [0015], “ANN 100 may be trained to determine the respective MRI data sampling patterns and/or reconstruction techniques that are applied to MRI images 104a-104c based on quality criteria 106 associated with the MRI images (e.g., associated with an MRI study based on the multi-contrast images)… Quality criteria 106 may include, for example, an overall acceleration rate associated with the MRI study (e.g., for generating MRI images 104a-104c)”)
comprising: establishing a spatially resolved image quality metric for a magnetic resonance image generated with the image-generating procedure; evaluating the image quality metric (Chen, Paragraph [0015], “ANN 100 may be trained to determine the respective MRI data sampling patterns and/or reconstruction techniques that are applied to MRI images 104a-104c based on quality criteria 106 associated with the MRI images (e.g., associated with an MRI study based on the multi-contrast images)… Quality criteria 106 may include, for example, an overall acceleration rate associated with the MRI study (e.g., for generating MRI images 104a-104c), an overall scan time associated with the MRI study, respective image qualities of MRI images 104a-104c, a quality metric associated with a downstream application that utilizes one or more of MRI images 104a-104c, and/or the like.”)
Chen does not explicitly teach using at least one measure criterion with which at least one notification and/or adaptation measure is associated; and carrying out the at least one notification and/or adaptation measure for each fulfilled measure criterion.
Middlebrooks teaches using at least one measure criterion with which at least one notification and/or adaptation measure is associated; and carrying out the at least one notification and/or adaptation measure for each fulfilled measure criterion. (Middlebrooks, Paragraph[0047], “Similarly, responsive to determining that values of the rate of change are below the second configurable threshold, the assessment computing entity 100 may classify the sequential data and/or an associated MRI scan as non-satisfactory, low quality and/or the like. However, responsive to determining that values of the of the rate of change of sequential data are below the second configurable threshold and above the first configurable threshold, the assessment computing entity 100 may classify the sequential data and/or an associated MRI scan as potentially-satisfactory, average quality and/or the like… n an example embodiment, the notification may be provided by a light source such as an LED indicator light (e.g., disposed on the control panel of the scanner and/or the like), on a display device (e.g., a user interface of the assessment computing entity 100, the display 316, and/or the like), and/or through some other display/indicator means. In some implementations, the indications may be provided continuously”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Middlebrooks into Chen because by utilizing means to notify a user or operator of a device of the quality level of the MRI scan will allow the user to perform additional activities depending on the indication of the result.
Therefore it would have been obvious to one of ordinary skill to combine the two references to obtain the invention in Claim 1.
As per Claim 8, Chen in view of Middlebrooks teaches the method as claimed in claim 1, wherein the at least one notification measure comprises an output of a warning and/or a notification to a user. (Middlebrooks, Paragraph[0047], “the notification may be provided by a light source such as an LED indicator light (e.g., disposed on the control panel of the scanner and/or the like), on a display device (e.g., a user interface of the assessment computing entity 100, the display 316, and/or the like), and/or through some other display/indicator means.”)
The rationale applied to the rejection of claim 1 has been incorporated herein.
As per Claim 14, Chen in view of Middlebrooks teaches the magnetic resonance apparatus, comprising a controller configured to carry out a method as claimed in claim 1. (Chen, Paragraph [0034])
The rationale applied to the rejection of claim 1 has been incorporated herein.
As per Claim 15, Chen in view of Middlebrooks teaches the non-transitory electronically readable data carrier on which a computer program is stored, wherein the computer program carries out steps of the method as claimed in claim 1 when the program is executed on a controller of a magnetic resonance apparatus. (Chen, Paragraph [0034]-[0035])
The rationale applied to the rejection of claim 1 has been incorporated herein.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks as applied to Claim 1 and further in view of Koch et al. US2018/0292491 hereinafter referred to as Koch.
As per Claim 3, Chen in view of Middlebrooks teaches the method as claimed in claim 1,
comprising a complete sampling of a lower region of k-space to be sampled and/or for establishing reconstruction parameters to be used in the reconstruction procedure and/or from the magnetic resonance image. (Chen, Paragraph [0013])
Chen in view of Middlebrooks does not explicitly teach wherein the image quality metric is established from magnetic resonance data of a prescan,
Koch teaches wherein the image quality metric is established from magnetic resonance data of a prescan, (Koch, Paragraph [0016], “optimizing the efficiency of MRI scanning when metallic implants are a factor. For example, the calibration data contains data acquired at a number of different resonance frequency offsets. The calibration data acquired with this Initial “pre-scan,” or calibration scan” and Paragraph [0021], “Based on the calibration data, a field map, or off-resonance map, is computed, as indicated at step 104” and Paragraph [0023], “If it is determined that artifact reduction is unnecessary, then the method proceeds by computing or otherwise providing the optimal settings (e.g., receiver bandwidth, number of averages) for a non-3D-MSI acquisition, as indicated at step 108”, quality metric is considered the determination of the optimal settings utilizing the prescan/calibration data)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Koch into Chen in view of Middlebrooks because by performing a pre-scan will provide calibration data that will assist in the optimizing the efficiency of MRI scanning.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 3.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks and Koch et al. US2018/0292491 hereinafter referred to as Koch as applied to Claim 3 and further in view of Jin et al. US2016/0242712 hereinafter referred to as Jin.
As per Claim 4, Chen in view of Middlebrooks and Koch teaches the method as claimed in claim 3,
Chen in view of Middlebrooks and Koch does not explicitly teach wherein as the image quality metric, a geometry factor map and/or a noise map, and/or an SNR map of a signal-to-noise ratio
Jin teaches wherein as the image quality metric, a geometry factor map and/or a noise map, and/or an SNR map of a signal-to-noise ratio (Jin, Paragraph[0029], “In this embodiment, the noise estimates are noise variance maps and the dose estimates are dose maps, but are not limited. For example, any map of an image quality metric may be suitable to use with the present method”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Jin into Chen in view of Middlebrooks and Koch because by utilizing a noise map as a quality metric will be suitable for determining the quality of the image.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 4.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks and Koch et al. US2018/0292491 hereinafter referred to as Koch as applied to Claim 3 and further in view of Collazo et al. US2023/0274562 hereinafter referred to as Collazo.
As per Claim 5, Chen in view of Middlebrooks and Koch teaches the method as claimed in claim 3,
Chen in view of Middlebrooks and Koch does not explicitly teach wherein a confidence map of the magnetic resonance image is established as the image quality metric, using a trained confidence establishment function.
Collazo teaches wherein a confidence map of the magnetic resonance image is established as the image quality metric, using a trained confidence establishment function. (Collazo, Paragraph [0091], “Extracting the per-pixel confidence vote values and using them to construct a confidence map of each sample could provide a quality metric similar that helps the expert determine where to focus attentions”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Collazo into Chen in view of Middlebrooks and Koch because by utilizing a confidence map as a quality metric will be suitable for determining the quality of the image.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 5.
Claims 9-10 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks as applied to Claim 1 and further in view of Wang et al. US2024/0257949 hereinafter referred to as Wang.
As per Claim 9, Chen in view of Middlebrooks teaches the method as claimed in claim 1,
Chen in view of Middlebrooks does not explicitly teach wherein at least one notification and/or adaptation measure comprises establishment of at least one proposal for at least one recording parameter of a recording procedure and/or at least one reconstruction parameter of the reconstruction procedure, wherein the at least one proposal is used automatically and/or after confirmation by a user after an output to the user for adapting image- generating parameters and an image generation takes place.
Wang teaches wherein at least one notification and/or adaptation measure comprises establishment of at least one proposal for at least one recording parameter of a recording procedure and/or at least one reconstruction parameter of the reconstruction procedure, wherein the at least one proposal is used automatically and/or after confirmation by a user after an output to the user for adapting image- generating parameters and an image generation takes place. (Wang, Paragraph [0058], “The user input may be related to the operation of the MRI system (e.g., certain threshold settings for controlling program execution, parameters for controlling the joint estimation of coil sensitivity and image reconstruction, etc). The user input may be related to various operations or settings about the detection and classification system 740. The user input may include, for example, a selection of a target structure or ROI, training parameters, setting an image acceleration parameter, displaying settings of a reconstructed image, customizable display preferences, selection of an acquisition scheme, and various others”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Wang into Chen in view of Middlebrooks because by providing a user interface to allow the user to provide input to parameters will result in the usage of the MRI system to the user’s specifications and needs.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 9.
As per Claim 10, Chen in view of Middlebrooks and Wang teaches the method as claimed in claim 9, wherein the establishment of the proposal takes place such that at least a previously fulfilled measure criterion is no longer fulfilled when using the proposal, and no further measure criterion is fulfilled. (Wang, Paragraph [0058], “The user input may be related to the operation of the MRI system (e.g., certain threshold settings for controlling program execution, parameters for controlling the joint estimation of coil sensitivity and image reconstruction, etc). The user input may be related to various operations or settings about the detection and classification system 740. The user input may include, for example, a selection of a target structure or ROI, training parameters, setting an image acceleration parameter, displaying settings of a reconstructed image, customizable
The rationale applied to the rejection of claim 9 has been incorporated herein.
As per Claim 12, Chen in view of Middlebrooks and Wang teaches the method as claimed in claim 9, wherein for exclusively at least one proposal regarding at least one reconstruction parameter, for this an improvement image is generated in a renewed reconstruction procedure and an improvement image quality metric is established, wherein for an improvement image quality metric indicating an improvement relative to the original image quality metric of the magnetic resonance image, the original magnetic resonance image is discarded, and the improvement image is used as the magnetic resonance image. (Middlebrooks, Paragraph [0047] and Wang, Paragraph [0058], “The user input may be related to various operations or settings about the detection and classification system 740. The user input may include, for example, a selection of a target structure or ROI, training parameters, setting an image acceleration parameter, displaying settings of a reconstructed image, customizable display preferences, selection of an acquisition scheme, and various others”)
The rationale applied to the rejection of claim 9 has been incorporated herein.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks and Wang et al. US2024/0257949 hereinafter referred to as Wang as applied to Claim 1 and further in view of Koch et al. US2018/0292491 hereinafter referred to as Koch.
As per Claim 11, Chen in view of Middlebrooks and Wang teaches the method as claimed in claim 9, proposal image quality metrics are established and are visualized to a user for selection of at least one of the at least one proposal regarding recording parameters. (Wang, Paragraph [0058], “The user input may be related to the operation of the MRI system (e.g., certain threshold settings for controlling program execution, parameters for controlling the joint estimation of coil sensitivity and image reconstruction, etc). The user input may be related to various operations or settings about the detection and classification system 740. The user input may include, for example, a selection of a target structure or ROI, training parameters, setting an image acceleration parameter, displaying settings of a reconstructed image, customizable display preferences, selection of an acquisition scheme, and various others”)
Chen in view of Middlebrooks and Wang does not explicitly teach wherein for a plurality of proposals using magnetic resonance data of a prescan,
Koch teaches wherein for a plurality of proposals using magnetic resonance data of a prescan, (Koch, Paragraph [0016], “optimizing the efficiency of MRI scanning when metallic implants are a factor. For example, the calibration data contains data acquired at a number of different resonance frequency offsets. The calibration data acquired with this Initial “pre-scan,” or calibration scan” and Paragraph [0021], “Based on the calibration data, a field map, or off-resonance map, is computed, as indicated at step 104” and Paragraph [0023], “If it is determined that artifact reduction is unnecessary, then the method proceeds by computing or otherwise providing the optimal settings (e.g., receiver bandwidth, number of averages) for a non-3D-MSI acquisition, as indicated at step 108”, quality metric is considered the determination of the optimal settings utilizing the prescan/calibration data)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Koch into Chen in view of Middlebrooks and Wang because by performing a pre-scan will provide calibration data that will assist in the optimizing the efficiency of MRI scanning.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 11.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. US2023/0184860 hereinafter referred to as Chen in view of Middlebrooks et al. US2019/0066297 hereinafter referred to as Middlebrooks as applied to Claim 1 and further in view of Witschey et al. US2017/0332981 hereinafter referred to as Witschey.
As per Claim 13, Chen in view of Middlebrooks teaches the method as claimed in claim 1,
Chen in view of Middlebrooks does not explicitly teach wherein at least one adaptation measure relates to recording of additional raw data, reducing undersampling in an additional recording procedure.
Witschey teaches wherein at least one adaptation measure relates to recording of additional raw data, reducing undersampling in an additional recording procedure. (Witschey, Paragraph [0052], “One application of this method is improving cardiovascular MRI image examinations by combining new data with additional data from previous periods to improve image quality, guaranteeing that the sampling trajectory is uniform, reducing Nyquist undersampling artifacts, and permitting continuous image re-construction and display in real-time”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Witschey into Chen in view of Middlebrooks because by combining new data with additional data from previous periods to improve image quality will guaranteeing that the sampling trajectory is uniform, reduce Nyquist undersampling artifacts, and permit continuous image re-construction and display in real-time.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 13.
Allowable Subject Matter
Claims 2, 6-7 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/MING Y HON/Primary Examiner, Art Unit 2666