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公开(公告)号：US20200037962A1
公开(公告)日：2020-02-06
申请号：US16051723
申请日：2018-08-01
Applicant: General Electric Company
Inventor： Dattesh Dayanand Shanbhag , Chitresh Bhushan , Arathi Sreekumari , Andre de Almeida Maximo , Rakesh Mullick , Thomas Kwok-Fah Foo
Abstract: The present disclosure relates to use of a workflow for automatic prescription of different radiological imaging scan planes across different anatomies and modalities. The automated prescription of such imaging scan planes helps ensure contiguous visualization of the different landmark structures. Unlike prior approaches, the disclosed technique determines the necessary planes using the localizer images itself and does not explicitly segment or delineate the landmark structures to perform plane prescription.
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公开(公告)号：USD854695S1
公开(公告)日：2019-07-23
申请号：US29626578
申请日：2017-11-17
Applicant: General Electric Company
Designer： Mahendra Madhukar Patil , Chandan Kumar Aladahalli , Krishna Shriram , Rakesh Mullick , Amit Singh
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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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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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Patent Agency Ranking
16.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：US20150282782A1
公开(公告)日：2015-10-08
申请号：US14247265
申请日：2014-04-08
Applicant: General Electric Company
Inventor： Fei Zhao , Vivek Prabhakar Vaidya , Rakesh Mullick , Soma Biswas , Chuyang Ye
IPC: A61B8/08
CPC classification number: A61B8/0825 , A61B8/483 , A61B8/5207 , A61B8/5223 , A61B8/5269 , G06F19/321 , G06T7/0012 , G06T7/12 , G06T2207/10136 , G06T2207/20116 , G06T2207/30068 , G16H50/20
Abstract: A method for detecting a lesion in an anatomical region of interest is presented. The method includes identifying one or more candidate mass regions in each of a plurality of 3D ultrasound images acquired at different view angles from the anatomical region of interest. Single-view features corresponding to each candidate mass region are identified. For a candidate mass region, a similarity metric between the single-view features corresponding to the candidate mass region and the single-view features corresponding to the other candidate mass regions is determined. The candidate mass region is classified based at least on the similarity metric. A system for imaging and a non-transitory computer readable media for detection of the lesion are also presented.
Abstract translation: 提出了一种用于检测感兴趣的解剖学区域中的病变的方法。 该方法包括识别从与感兴趣的解剖区域不同的视角获取的多个3D超声图像中的每一个中的一个或多个候选质量区域。 识别与每个候选质量区域对应的单视图特征。 对于候选质量区域，确定对应于候选质量区域的单视图特征与对应于其他候选质量区域的单视图特征之间的相似性度量。 至少基于相似性度量对候选质量区进行分类。 还提出了用于成像的系统和用于检测病变的非暂时计算机可读介质。
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公开(公告)号：US11432803B2
公开(公告)日：2022-09-06
申请号：US16523098
申请日：2019-07-26
Applicant: General Electric Company
Inventor： Christian Fritz Perrey , Suvadip Mukherjee , Nitin Singhal , Rakesh Mullick
Abstract: A system (e.g., an ultrasound imaging system) is provided. The system includes an ultrasound probe configured to acquire three-dimensional (3D) ultrasound data of a volumetric region of interest (ROI). The system further includes a display, a memory configured to store programmed instructions, and a controller circuit. The controller circuit includes one or more processors. The controller circuit is configured to execute the programmed instructions stored in the memory. When executing the programmed instructions, the controller circuit performs a plurality of operations. The operations includes collecting the 3D ultrasound data from an ultrasound probe and identifying a select set of the 3D ultrasound data corresponding to an object of interest within the volumetric ROI. The operations further include segmenting the object of interest from the select set of the 3D ultrasound data, generating a visualization plane of the object of interest, and displaying the visualization plane on the display.
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公开(公告)号：US20180032681A1
公开(公告)日：2018-02-01
申请号：US15224364
申请日：2016-07-29
Applicant: General Electric Company
Inventor： Chandan Kumar Mallappa Aladahalli , Dattesh Dayanand Shanbhag , Rakesh Mullick , Venkata Veerendra Nadh Chebrolu , Ersin Bayram
IPC: G06F19/00 , G06F3/0484 , G06F3/0482
Abstract: The present disclosure relates to a method for assessing biological features, the method that includes rendering a graphical user interface allowing a user to select patient cohort information defining one or more characteristics of a patient cohort and allowing a user to select an analysis technique from a plurality of analysis techniques, wherein the analysis technique operates on the patient data from both the first data acquisition modality and the second data acquisition modality to generate a derived variable. The method also includes allowing a user to define a threshold for the derived variable to define a first patient group above the threshold and a second patient group below the threshold for each patient of a patient cohort.
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公开(公告)号：US20170371010A1
公开(公告)日：2017-12-28
申请号：US15532680
申请日：2015-12-02
Applicant: General Electric Company
Inventor： Dattesh Dayanand Shanbhag , Rakesh Mullick , Sheshadri Thiruvenkadam , Florian Wiesinger , Sudhanya Chatterjee , Kevin Matthew Koch
CPC classification number: G01R33/243 , A61B5/0035 , A61B5/055 , G01R33/481 , G01R33/4816 , G01R33/5608 , G01R33/56536
Abstract: An imaging system and method are disclosed. An MR image and measured B0 field map of a target volume in a subject are reconstructed, where the MR image includes one or more bright and/or dark regions. One or more distinctive constituent materials corresponding to the bright regions are identified. Each dark region is iteratively labeled as one or more ambiguous constituent materials. Susceptibility values corresponding to each distinctive and iteratively labeled ambiguous constituent material is assigned. A simulated B0 field map is iteratively generated based on the assigned susceptibility values. A similarity metric is determined between the measured and simulated B0 field maps. Constituent materials are identified in the dark regions based on the similarity metric to ascertain corresponding susceptibility values. The MRI data is corrected based on the assigned and ascertained susceptibility values. A diagnostic assessment of the target volume is determined based on the corrected MRI data.
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