DETAILED ACTION
Notice of AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Request for Continued Examination
2. 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1.114, and the fee set forth in 37 CFR 1.17© has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 02/27/2026 has been entered.
Response to Arguments
3. Applicant’s remarks received on 02/11/2026 with respect to the amended independent claims have been acknowledged and are moot in view of a new ground of rejected necessitated by the corresponding amendment. Currently claims 1-5 and 7-20 remain rejected; and claim 6 is cancelled.
Response to Amendment
Claim Rejections - 35 USC § 103
4. 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.
51066.. Claims 1-5, 7, 8, and 10-18 are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al (Automatic View Planning for Cardiac MRI Acquisition) and in further view of Lu 152’ (US Pub: 2012/0121152) and Crooks et al (US Patent: 4,746,863).
Regarding claim 1 (Currently Amended), Lu et al teaches: A computer-implemented method for determining an orientation of at least one diagnostically relevant sectional plane for heart imaging in a three-dimensional magnetic resonance imaging image dataset, the computer- implemented method comprising: providing the three-dimensional magnetic resonance imaging image dataset [page 480: 2.1: p01]; applying a trained function to the three-dimensional magnetic resonance imaging image dataset to determine a position of at least one landmark [page 480: p04]; determining the orientation of the at least one diagnostically relevant sectional plane as a function of the at least one landmark [page 483: p01, p03].
Lu et al provides scanner with plane prescription used for acquisition in terms of short/long axis view [page 483: p01]. In the same field of endeavor, Lu 152’ teaches: providing the orientation of the at least one diagnostically relevant sectional plane by providing at least one first scanning parameter value for controlling a magnetic resonance imaging system for recording a two-dimensional sectional image of the at least one diagnostically relevant sectional plane [p0028, p0029, p0034 (2D plan)].
Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of the two to implement Lu et al’s landmark based cardiac plane with scan prescription framework of Lu 152’ for automatically acquiring 2D cardiac views.
Lu et al in view of Lu 152’ does not specify parameter for steepness of magnetic field gradient. In the same field of endeavor, Crooks et al teaches: the at least one first scanning parameter including a direction and a steepness of a magnetic field gradient [col 6: lines 65-67, col 7: lines 1-4, 29-36, 54-57]. Therefore, given Crooks et al’s prescription on MRI control parameters used to realize a selected slice/plane with gradient direction to the plane and slope of gradient, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to use MRI control parameter to realized a plane in a scanner with automation.
Regarding claim 2 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Lu et al further teaches: The computer-implemented method as claimed in claim 1, wherein the three-dimensional magnetic resonance imaging image dataset maps at least one part of a heart, and wherein the three-dimensional magnetic resonance imaging image dataset is an overview scan of the at least one part of the heart [page 479: introduction, page 480: p01].
Regarding claim 3 (original), the rationale applied to the rejection of claim 2 has been incorporated herein. Lu et al further teaches: The computer-implemented method as claimed in claim 2, wherein the at least one landmark is one of an apex, a mitral valve, an aortic valve, a pulmonary valve, or a tricuspid valve [page 479: introduction, page 480: p01].
Regarding claim 4 (original), the rationale applied to the rejection of claim 2 has been incorporated herein. Lu et al further teaches: The computer-implemented method as claimed in claim 2, wherein the at least one diagnostically relevant sectional plane is one of a four chamber plane, a three chamber plane, a two chamber plane, a vertical long axis, a horizontal long axis, or a short axis [abstract].
Regarding claim 5 (previously presented), the rationale applied to the rejection of claim 1 has been incorporated herein. Lu et al further teaches: The computer-implemented method as claimed in claim 1, wherein the applying of the trained function comprises: determining the position of the at least one landmark in the three-dimensional magnetic resonance imaging image dataset as a probability distribution for the position of the at least one landmark [page 482: p04].
Regarding claim 7 (previously presented), the rationale applied to the rejection of claim 1 has been incorporated herein. Lu 152’ further teaches: The computer-implemented method as claimed in claim 1, wherein the at least one first scanning parameter value is derived from the orientation of the at least one diagnostically relevant sectional plane [p0028, p0029].
Regarding claim 8 (previously presented), the rationale applied to the rejection of claim 1 has been incorporated herein. Huang further teaches: The computer-implemented method as claimed in claim 1, further comprising: recording the two-dimensional sectional image with the magnetic resonance imaging system as a function of the at least one first scanning parameter value; and providing the two-dimensional sectional image [p0152 (Determination of target scanning parameters for optimal orientation of an image is based on predetermined mathematical correlation.)].
Regarding claim 10 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Lu et al further teach: The computer-implemented method as claimed in claim 1, wherein the trained function is based on at least one of a neural convolutional network or a U-Network [page 480: p04, page 482: 2.2].
Claim 11 (previously presented) has been analyzed and rejected with regard to claim 1 with Lu et al’s further teaching on: receiving at least one annotated three-dimensional training image dataset, wherein the at least one annotated three-dimensional training image dataset is based on the at least one three-dimensional training image dataset, and wherein the position of the at least one landmark is annotated in the at least one annotated three-dimensional training image dataset; training a function as a function of the at least one three-dimensional training image dataset and the at least one annotated three-dimensional training image dataset; and providing the trained function [page 482: 2.2].
Regarding claim 12 (original), the rationale applied to the rejection of claim 11 has been incorporated herein. Lu et al further teaches: The computer-implemented method as claimed in claim 11, further comprising: manually annotating the at least one three-dimensional training image dataset to create the at least one annotated three-dimensional training image dataset [page 482: 2.2].
Claim 13 (currently amended) has been analyzed and rejected with regard to claim 1.
Regarding claim 14 (previously presented), the rationale applied to the rejection of claim 13 has been incorporated herein. Lu et al further teaches: A magnetic resonance imaging system comprising: the determining system as claimed in claim 13, wherein the magnetic resonance imaging system is configured to acquire at least one of the three-dimensional magnetic resonance imaging image dataset or a two-dimensional sectional image [page 482: 2.2].
Claim 15 (original) has been analyzed and rejected with regard to claim 1 and in accordance with Lu 152’s further teaching on: A non-transitory computer program product including a computer program, which is loadable into a memory of a determining system, the computer program including program segments that, when executed by the determining system, cause the determining system to perform the computer-implemented method as claimed in claim 1 [p0038].
Claim 16 (original) has been analyzed and rejected with regard to claim 15.
Regarding claim 17 (previously presented), the rationale applied to the rejection of claim 2 has been incorporated herein. Claim 17 has been analyzed and rejected with regard to claim 15.
Regarding claim 18 (original), the rationale applied to the rejection of claim 7 has been incorporated herein. Claim 18 has been analyzed and rejected with regard to claim 8.
61066.. Claims 9, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al (Automatic View Planning for Cardiac MRI Acquisition) and Lu 152’ (US Pub: 2012/0121152), and Crooks et al (US Patent: 4,746,863); and in further view of Traverso et al (EP Pub: 3373024).
Regarding claim 9 (currently amended), the rationale applied to the rejection of claim 1 has been incorporated herein. Claim 9 has been analyzed and are rejected with regard to claim 1. Lu et al in view of Lu 152’ and Crooks et al does not teach a 3D perpendicular to a sectional plane. In the same field of endeavor, Traverso et al teaches: The computer-implemented method as claimed in claim 1, further comprising: determining an extent of a three-dimensional volume image perpendicular to the at least one diagnostically relevant sectional plane, wherein the three-dimensional volume image is spanned by the at least one diagnostically relevant sectional plane and the extent [p0004]. Traverso et al also disclose: providing at least one scanning parameter value for controlling a magnetic resonance imaging system for recording the three-dimensional volume image, wherein the at least one first scanning parameter value is further derived from the orientation of the at least one diagnostically relevant sectional plane and the extent; recording the three-dimensional volume image with the magnetic resonance imaging system as a function of the at least one first scanning parameter value; and providing the three-dimensional volume image [p0021, p0022].
Therefore, given Lu et al in view of Lu 152’s prescription on various scanning parameter values and planning short axis stack from LV base to apex and determining viewing parameters for each slice based on detected LV long axis and Traveso et al’s teaching on generating 3D perpendicular to a sectional plane and adjusting scanning parameters as a function related to determining plane orientation, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to control a MRI to obtain a 2D or 3D sectional/perpendicular images by changing scanning parameters for properly tracing landmarks under various heart conditions.
Regarding claim 19 (currently amended), the rationale applied to the rejection of claim 5 has been incorporated herein. Claim 19 has been analyzed and rejected with regard to claim 9.
Regarding claim 20 (original), the rationale applied to the rejection of claim 9 has been incorporated herein. Claim 20 has been rejected with regard to claim 10.
Contact
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/Fan Zhang/
Patent Examiner, Art Unit 2682