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公开(公告)号：US20200279369A1
公开(公告)日：2020-09-03
申请号：US16645872
申请日：2018-09-24
发明人： Timor KADIR , Lyndsey PICKUP , Vaclav POTESIL , Jerome DECLERCK
摘要： A Computer Aided Diagnosis, CADx, system (200) is described that comprises: at least one input (210, 212, 214) configured to provide at least one input medical image; and a CADx processing engine (220) configured to receive and process the at least one input medical image and produce at least one CADx score. A CADx score mapping circuit is operably coupled to the CADx processing engine (220) and configured to: map the at least one CADx score to a risk adjusted virtual score; and generate an output (235) of at least the risk adjusted virtual score associated with the processed at least one input medical image. The at least one CADx score and the risk adjusted virtual score correspond to an equivalent risk of condition or disease associated with a patient.
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公开(公告)号：US11704792B2
公开(公告)日：2023-07-18
申请号：US16645872
申请日：2018-09-24
发明人： Timor Kadir , Lyndsey Pickup , Vaclav Potesil , Jerome Declerck
CPC分类号： G06T7/0012 , G16H30/40 , G16H50/20 , G16H50/30 , G16H50/70 , G06T2207/10081 , G06T2207/10104 , G06T2207/20081 , G06T2207/20084 , G06T2207/30064
摘要： A Computer Aided Diagnosis, CADx, system (200) is described that comprises: at least one input (210, 212, 214) configured to provide at least one input medical image; and a CADx processing engine (220) configured to receive and process the at least one input medical image and produce at least one CADx score. A CADx score mapping circuit is operably coupled to the CADx processing engine (220) and configured to: map the at least one CADx score to a risk adjusted virtual score; and generate an output (235) of at least the risk adjusted virtual score associated with the processed at least one input medical image. The at least one CADx score and the risk adjusted virtual score correspond to an equivalent risk of condition or disease associated with a patient.
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3.发明授权System and method for whole body landmark detection, segmentation and change quantification in digital images 有权数字图像全身地标检测，分割和变化量化的系统和方法公开(公告)号：US07876938B2
公开(公告)日：2011-01-25
申请号：US11542477
申请日：2006-10-03
申请人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
发明人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
CPC分类号： G06T7/174 , G06T7/155 , G06T7/33 , G06T7/38 , G06T2207/10072 , G06T2207/20016 , G06T2207/20081 , G06T2207/20164 , G06T2207/30004 , G06T2207/30204
摘要： A method for segmenting digitized images includes providing a training set comprising a plurality of digitized whole-body images, providing labels on anatomical landmarks in each image of said training set, aligning each said training set image, generating positive and negative training examples for each landmark by cropping the aligned training volumes into one or more cropping windows of different spatial scales, and using said positive and negative examples to train a detector for each landmark at one or more spatial scales ranging from a coarse resolution to a fine resolution, wherein the spatial relationship between a cropping windows of a coarse resolution detector and a fine resolution detector is recorded.
摘要翻译： 用于分割数字化图像的方法包括提供包括多个数字化的全身图像的训练集合，在所述训练集合的每个图像中的解剖学标志上提供标签，对准每个所述训练集合图像，为每个界标生成正和负训练样本 通过将对准的训练量裁剪成不同空间尺度的一个或多个裁剪窗口，并且使用所述正和负的示例来在从粗分辨率到精细分辨率的一个或多个空间尺度上训练每个地标的检测器，其中空间 记录粗分辨率检测器的裁切窗与精细分辨率检测器之间的关系。
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4.发明授权Systems and methods for automatic change quantification for medical decision support 有权用于医疗决策支持的自动变更量化的系统和方法公开(公告)号：US07724930B2
公开(公告)日：2010-05-25
申请号：US11590451
申请日：2006-10-31
申请人： Xiang Zhou , Arun Krishnan , Alok Gupta , Vaclav Potesil
发明人： Xiang Zhou , Arun Krishnan , Alok Gupta , Vaclav Potesil
CPC分类号： G06T7/0012 , G06T7/38 , G06T2207/30004
摘要： A method of automatic change quantification for medical decision support includes: automatically detecting a structure in a set of medical images; characterizing the detected structure including modeling of deformation characteristics of the detected structure; matching images based on the characterization of the detected structure, wherein a size measure of the detected structure is constrained according to the deformation characteristics; and quantifying a change in the detected structure.
摘要翻译： 用于医疗决策支持的自动变化量化的方法包括：自动检测一组医学图像中的结构; 表征检测到的结构，包括检测结构的变形特性的建模; 基于检测结构的表征匹配图像，其中检测结构的尺寸测量根据变形特性被约束; 并量化检测结构的变化。
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公开(公告)号：US20200279649A1
公开(公告)日：2020-09-03
申请号：US16645888
申请日：2018-09-24
发明人： Timor KADIR , Lyndsey PICKUP , Vaclav POTESIL , Jerome DECLERCK
摘要： A Computer Aided Diagnosis, CAD, training system (400) is described for training a CAD device (310) to receive and process at least one input medical image and produce an output that indicates a probability of a medical condition of a patient. The CAD device (310) comprises: an input circuit (305) configured to receive and assemble training data that comprises: medical data of patients that have been identified as having at least one medical condition, and medical data of patients that have been identified as not having the at least one medical condition. A parsing circuit (315) is configured to: separate the assembled training data into data sets, such that a first data set contains only the medical data of patients that have the at least one medical condition and a second data set contains only the medical data of patients that do not have the condition; and parse at least one of the data sets into at least two subsets (328), whereby a first subset is distinguished over a second subset of the at least two subsets (328) by at least one attribute. A data classifier circuit (330) is configured to associate different weights to the separated assembled training data, such that the first subset is prioritised during training of the CAD device.
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6.发明申请Systems and methods for automatic change quantification for medical decision support 有权用于医疗决策支持的自动变更量化的系统和方法公开(公告)号：US20070122018A1
公开(公告)日：2007-05-31
申请号：US11590451
申请日：2006-10-31
申请人： Xiang Zhou , Arun Krishnan , Alok Gupta , Vaclav Potesil
发明人： Xiang Zhou , Arun Krishnan , Alok Gupta , Vaclav Potesil
CPC分类号： G06T7/0012 , G06T7/38 , G06T2207/30004
摘要： A method of automatic change quantification for medical decision support includes: automatically detecting a structure in a set of medical images; characterizing the detected structure including modeling of deformation characteristics of the detected structure; matching images based on the characterization of the detected structure, wherein a size measure of the detected structure is constrained according to the deformation characteristics; and quantifying a change in the detected structure.
摘要翻译： 用于医疗决策支持的自动变化量化的方法包括：自动检测一组医学图像中的结构; 表征检测到的结构，包括检测结构的变形特性的建模; 基于检测结构的表征匹配图像，其中检测结构的尺寸测量根据变形特性被约束; 并量化检测结构的变化。
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7.发明申请System and method for whole body landmark detection, segmentation and change quantification in digital images 有权数字图像全身地标检测，分割和变化量化的系统和方法公开(公告)号：US20070081712A1
公开(公告)日：2007-04-12
申请号：US11542477
申请日：2006-10-03
申请人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
发明人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
IPC分类号： G06K9/00
CPC分类号： G06T7/174 , G06T7/155 , G06T7/33 , G06T7/38 , G06T2207/10072 , G06T2207/20016 , G06T2207/20081 , G06T2207/20164 , G06T2207/30004 , G06T2207/30204
摘要： A method for segmenting digitized images includes providing a training set comprising a plurality of digitized whole-body images, providing labels on anatomical landmarks in each image of said training set, aligning each said training set image, generating positive and negative training examples for each landmark by cropping the aligned training volumes into one or more cropping windows of different spatial scales, and using said positive and negative examples to train a detector for each landmark at one or more spatial scales ranging from a coarse resolution to a fine resolution, wherein the spatial relationship between a cropping windows of a coarse resolution detector and a fine resolution detector is recorded.
摘要翻译： 用于分割数字化图像的方法包括提供包括多个数字化的全身图像的训练集合，在所述训练集合的每个图像中的解剖学标志上提供标签，对准每个所述训练集合图像，为每个界标生成正和负训练样本 通过将对准的训练量裁剪成不同空间尺度的一个或多个裁剪窗口，并且使用所述正和负的示例来在从粗分辨率到精细分辨率的一个或多个空间尺度上训练每个地标的检测器，其中空间 记录粗分辨率检测器的裁切窗与精细分辨率检测器之间的关系。
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