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公开(公告)号：US10997724B2
公开(公告)日：2021-05-04
申请号：US16469373
申请日：2017-12-14
Applicant: General Electric Company
Inventor： Hariharan Ravishankar , Vivek Prabhakar Vaidya , Sheshadri Thiruvenkadam , Rahul Venkataramani , Prasad Sudhakar
Abstract: A method for image segmentation includes receiving an input image (102). The method further includes obtaining a deep learning model (104) having a triad of predictors (116, 118, 120). Furthermore, the method includes processing the input image by a shape model in the triad of predictors (116, 118, 120) to generate a segmented shape image (110). Moreover, the method includes presenting the segmented shape image via a display unit (128).
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公开(公告)号：US20190266448A1
公开(公告)日：2019-08-29
申请号：US16334091
申请日：2017-06-21
Applicant: General Electric Company
Inventor： Sheshadri Thiruvenkadam , Sohan Rashmi Ranjan , Vivek Prabhakar Vaidya , Hariharan Ravishankar , Rahul Venkataramani , Prasad Sudhakar
Abstract: A method for determining optimized deep learning architecture includes receiving a plurality of training images and a plurality of real time images corresponding to a subject. The method further includes receiving, by a medical practitioner, a plurality of learning parameters comprising a plurality of filter classes and a plurality of architecture parameters. The method also includes determining a deep learning model based on the plurality of learning parameters and the plurality of training images, wherein the deep learning model comprises a plurality of reusable filters. The method further includes determining a health condition of the subject based on the plurality of real time images and the deep learning model. The method also includes providing the health condition of the subject to the medical practitioner.
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公开(公告)号：US10262425B2
公开(公告)日：2019-04-16
申请号：US15637280
申请日：2017-06-29
Applicant: General Electric Company
Inventor： Chandan Kumar Mallappa Aladahalli , Krishna Seetharam Shriram , Dattesh Dayanand Shanbhag , Sheshadri Thiruvenkadam , Sandeep Suryanarayana Kaushik , Rakesh Mullick
Abstract: A method for synchronization of a longitudinal data set from a subject includes receiving a first ensemble registration estimate having a first reference image corresponding to a first image ensemble and receiving a second image ensemble different from the first image ensemble. The method includes determining a second reference image based on the second image ensemble and the first reference image. Further, the method includes determining a second ensemble registration estimate based on the first ensemble registration estimate, the second reference image, the first image ensemble and the second image ensemble using an optimization technique. The method further includes generating a synchronized image ensemble corresponding to the first image ensemble and the second image ensemble based on the second ensemble registration estimate. The method also includes determining a medical condition of the subject by a medical practitioner based on the synchronized image ensemble.
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Patent Agency Ranking
公开(公告)号：US20180197317A1
公开(公告)日：2018-07-12
申请号：US15400763
申请日：2017-01-06
Applicant: General Electric Company
Inventor： Lishui Cheng , Bruno Kristiaan Bernard De Man , Sheshadri Thiruvenkadam , Sangtae Ahn , Lin Fu , Hao Lai
CPC classification number: G06N3/08 , G06N3/0454 , G06T11/006 , G06T2211/421 , G06T2211/424
Abstract: The present discussion relates to the use of deep learning techniques to accelerate iterative reconstruction of images, such as CT, PET, and MR images. The present approach utilizes deep learning techniques so as to provide a better initialization to one or more steps of the numerical iterative reconstruction algorithm by learning a trajectory of convergence from estimates at different convergence status so that it can reach the maximum or minimum of a cost function faster.
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公开(公告)号：US20180005389A1
公开(公告)日：2018-01-04
申请号：US15637280
申请日：2017-06-29
Applicant: General Electric Company
Inventor： Chandan Kumar Mallappa Aladahalli , Krishna Seetharam Shriram , Dattesh Dayanand Shanbhag , Sheshadri Thiruvenkadam , Sandeep Suryanarayana Kaushik , Rakesh Mullick
CPC classification number: G06T7/33 , A61B5/0033 , A61B5/0073 , A61B5/0515 , A61B5/055 , A61B5/486 , A61B5/72 , G06F19/00 , G06F19/34 , G06Q50/24 , G06T7/0012 , G06T7/0016 , G06T7/11 , G06T7/32
Abstract: A method for synchronization of a longitudinal data set from a subject includes receiving a first ensemble registration estimate having a first reference image corresponding to a first image ensemble and receiving a second image ensemble different from the first image ensemble. The method includes determining a second reference image based on the second image ensemble and the first reference image. Further, the method includes determining a second ensemble registration estimate based on the first ensemble registration estimate, the second reference image, the first image ensemble and the second image ensemble using an optimization technique. The method further includes generating a synchronized image ensemble corresponding to the first image ensemble and the second image ensemble based on the second ensemble registration estimate. The method also includes determining a medical condition of the subject by a medical practitioner based on the synchronized image ensemble.
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公开(公告)号：US09760991B2
公开(公告)日：2017-09-12
申请号：US14786508
申请日：2014-04-21
Applicant: General Electric Company
Inventor： Sheshadri Thiruvenkadam , Rakesh Mullick , Sandeep Kaushik , Hua Qian , Dattesh Shanbhag , Florian Wiesinger
IPC: G06K9/00 , G06T7/00 , A61B5/055 , A61B6/03 , A61B8/13 , G06T5/20 , G06T7/11 , G06T7/12 , G06T7/149 , G06T7/174 , G06T7/136
CPC classification number: G06T7/0012 , A61B5/055 , A61B6/032 , A61B6/037 , A61B8/13 , G06T5/20 , G06T7/11 , G06T7/12 , G06T7/136 , G06T7/149 , G06T7/174 , G06T2207/10081 , G06T2207/10088 , G06T2207/10104 , G06T2207/20116 , G06T2207/30004 , G06T2207/30024 , G06T2210/41
Abstract: A system and method for estimating image intensity bias and segmentation tissues is presented. The system and method includes obtaining a first image data set and at least a second image data set, wherein the first and second image data sets are representative of an anatomical region in a subject of interest. Furthermore, the system and method includes generating a baseline bias map by processing the first image data set. The system and method also includes determining a baseline body mask by processing the second image data set. In addition, the system and method includes estimating a bias map corresponding to a sub-region in the anatomical region based on the baseline body mask. Moreover, the system and method includes segmenting one or more tissues in the anatomical region based on the bias map.
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17.发明申请SYSTEM AND METHOD FOR IMAGE INTENSITY BIAS ESTIMATION AND TISSUE SEGMENTATION 有权用于图像强度偏差估计和组织分类的系统和方法公开(公告)号：US20160071263A1
公开(公告)日：2016-03-10
申请号：US14786508
申请日：2014-04-21
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Sheshadri Thiruvenkadam , Rakesh Mullick , Sandeep Kaushik , Hua Qian , Dattesh Shanbhag , Florian Wiesinger
CPC classification number: G06T7/0012 , A61B5/055 , A61B6/032 , A61B6/037 , A61B8/13 , G06T5/20 , G06T7/11 , G06T7/12 , G06T7/136 , G06T7/149 , G06T7/174 , G06T2207/10081 , G06T2207/10088 , G06T2207/10104 , G06T2207/20116 , G06T2207/30004 , G06T2207/30024 , G06T2210/41
Abstract: A system and method for estimating image intensity bias and segmentation tissues is presented. The system and method includes obtaining a first image data set and at least a second image data set, wherein the first and second image data sets are representative of an anatomical region in a subject of interest. Furthermore, the system and method includes generating a baseline bias map by processing the first image data set. The system and method also includes determining a baseline body mask by processing the second image data set. In addition, the system and method includes estimating a bias map corresponding to a sub-region in the anatomical region based on the baseline body mask. Moreover, the system and method includes segmenting one or more tissues in the anatomical region based on the bias map.
Abstract translation: 提出了一种用于估计图像强度偏差和分割组织的系统和方法。 该系统和方法包括获得第一图像数据集和至少第二图像数据集，其中第一和第二图像数据集代表感兴趣对象中的解剖区域。 此外，该系统和方法包括通过处理第一图像数据集来生成基线偏置图。 该系统和方法还包括通过处理第二图像数据集来确定基线体掩模。 另外，该系统和方法包括基于基线体掩模估计对应于解剖区域中的子区域的偏置图。 此外，系统和方法包括基于偏置图分割解剖区域中的一个或多个组织。
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公开(公告)号：US20140233818A1
公开(公告)日：2014-08-21
申请号：US13777981
申请日：2013-02-26
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Sheshadri Thiruvenkadam , Navneeth Subamanian , Mithun Das Gupta
IPC: G06T7/00
CPC classification number: G06T7/0097 , G06T7/0012 , G06T7/12 , G06T7/149 , G06T7/174 , G06T2207/10016 , G06T2207/10132 , G06T2207/20116 , G06T2207/30048
Abstract: Methods and systems for segmentation in echocardiography are provided. One method includes obtaining echocardiographic images and defining a search space within the echocardiographic images using a pair of one-dimensional (1D) profiles. The method also includes using an energy based function constrained by non-local temporal priors within the defined search space to automatically segment a contour of a cardiac structure with the 1D profiles.
Abstract translation: 提供超声心动图分割的方法和系统。 一种方法包括获得超声心动图像并使用一对一维（1D）轮廓在超声心动图中定义搜索空间。 该方法还包括使用由限定的搜索空间内的非局部时间先验约束的基于能量的功能，以利用1D轮廓自动分割心脏结构的轮廓。
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