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公开(公告)号：EP4332603A2
公开(公告)日：2024-03-06
申请号：EP23218656.9
申请日：2016-11-29
申请人： Arterys Inc.
IPC分类号： G01R33/563
摘要： An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. A protected health information (PHI) service is provided which de-identifies medical study data and allows medical providers to control PHI data, and uploads the de-identified data to an analytics service provider (ASP) system. A web application is provided which merges the PHI data with the de-identified data while keeping control of the PHI data with the medical provider.
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公开(公告)号：EP4332603A3
公开(公告)日：2024-05-22
申请号：EP23218656.9
申请日：2016-11-29
申请人： Arterys Inc.
IPC分类号： G16H10/60 , G16H30/20 , G16H30/40 , A61B5/00 , A61B5/02 , A61B5/021 , A61B5/026 , A61B5/055 , G01R33/56 , G01R33/563
CPC分类号： A61B5/055 , A61B5/7207 , A61B5/0022 , A61B5/0044 , A61B5/02 , A61B5/02007 , A61B5/02014 , A61B5/021 , A61B5/026 , A61B5/725 , A61B2576/02320130101 , A61B5/7257 , G01R33/5608 , G01R33/56316 , G16H10/60 , A61B5/0263 , G16H30/20 , G16H30/40
摘要： An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. A protected health information (PHI) service is provided which de-identifies medical study data and allows medical providers to control PHI data, and uploads the de-identified data to an analytics service provider (ASP) system. A web application is provided which merges the PHI data with the de-identified data while keeping control of the PHI data with the medical provider.
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公开(公告)号：EP3380859A1
公开(公告)日：2018-10-03
申请号：EP16869356.2
申请日：2016-11-29
申请人： Arterys Inc.
发明人： GOLDEN, Daniel, Irving , AXERIO-CILIES, John , LE, Matthieu , TAERUM, Torin, Arni , LIEMAN-SIFRY, Jesse
CPC分类号： G01R33/5608 , G01R33/561 , G01R33/5613 , G01R33/56308 , G01R33/56316 , G06N3/02 , G06T7/0012 , G06T7/11 , G06T2207/10088 , G06T2207/10132 , G06T2207/20081 , G06T2207/20084 , G06T2207/30048
摘要： Systems and methods for automated segmentation of anatomical structures, such as the human heart. The systems and methods employ convolutional neural networks (CNNs) to autonomously segment various parts of an anatomical structure represented by image data, such as 3D MRI data. The convolutional neural network utilizes two paths, a contracting path which includes convolution/pooling layers, and an expanding path which includes upsampling/convolution layers. The loss function used to validate the CNN model may specifically account for missing data, which allows for use of a larger training set. The CNN model may utilize multi-dimensional kernels (e.g., 2D, 3D, 4D, 6D), and may include various channels which encode spatial data, time data, flow data, etc. The systems and methods of the present disclosure also utilize CNNs to provide automated detection and display of landmarks in images of anatomical structures.
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公开(公告)号：EP3380008A2
公开(公告)日：2018-10-03
申请号：EP16869358.8
申请日：2016-11-29
申请人： Arterys Inc.
发明人： BECKERS, Fabien , AXERIO-CILIES, John , TAERUM, Torin, Arni , HSIAO, Albert , DE FRANCESCO, Giovanni , BIDULOCK, Darryl , JUGDEV, Tristan , NEWTON, Robert
IPC分类号： A61B5/055
CPC分类号： A61B5/0263 , A61B5/0013 , A61B5/0022 , A61B5/0044 , A61B5/02 , A61B5/02007 , A61B5/02014 , A61B5/021 , A61B5/026 , A61B5/055 , A61B5/7203 , A61B5/7207 , A61B5/725 , A61B5/7257 , A61B2576/023 , G01R33/5608 , G01R33/56316 , G06T7/0012 , G06T7/269 , G06T2207/10076 , G06T2207/10088 , G06T2207/30104 , G16H10/60 , G16H30/20 , G16H30/40 , H04L9/3213 , H04L63/0209
摘要： An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: perform error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. An asynchronous command and imaging pipeline allows remote image processing and analysis in a timely and secure manner even with complicated or large medical imaging data sets and metadata.
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公开(公告)号：EP3380008B1
公开(公告)日：2020-09-09
申请号：EP16869358.8
申请日：2016-11-29
申请人： Arterys Inc.
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公开(公告)号：EP3629898A1
公开(公告)日：2020-04-08
申请号：EP18808993.2
申请日：2018-05-30
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公开(公告)号：EP3380971A1
公开(公告)日：2018-10-03
申请号：EP16869357.0
申请日：2016-11-29
申请人： Arterys Inc.
CPC分类号： A61B5/0263 , A61B5/0013 , A61B5/0022 , A61B5/0044 , A61B5/02 , A61B5/02007 , A61B5/02014 , A61B5/021 , A61B5/026 , A61B5/055 , A61B5/7203 , A61B5/7207 , A61B5/725 , A61B5/7257 , A61B2576/023 , G01R33/5608 , G01R33/56316 , G06T7/0012 , G06T7/269 , G06T2207/10076 , G06T2207/10088 , G06T2207/30104 , G16H30/20 , G16H30/40 , H04L9/3213 , H04L63/0209
摘要： An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: perform error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. An asynchronous command and imaging pipeline allows remote image processing and analysis in a timely and secure manner even with complicated or large medical imaging data sets and metadata.
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