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1. 发明申请

US20150227809A1 ANOMALY DETECTION IN MEDICAL IMAGERY 有权
标题翻译：医学图像异常检测
公开(公告)号：US20150227809A1
公开(公告)日：2015-08-13
申请号：US14178313
申请日：2014-02-12
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Pavel Kisilev
IPC分类号： G06K9/46 , G06T11/60
CPC分类号： G06K9/4671 , G06K9/4628 , G06K9/4642 , G06K9/481 , G06K9/6267 , G06T5/40 , G06T7/0012 , G06T7/13 , G06T2207/10088 , G06T2207/10116 , G06T2207/30068 , G06T2207/30096
摘要： A method comprising using at least one hardware processor for computing a patch distinctiveness score for each of multiple patches of a medical image, computing a shape distinctiveness score for each of multiple regions of the medical image, and computing a saliency map of the medical image, by combining the patch distinctiveness score and the shape distinctiveness score.
摘要翻译：一种方法，包括使用至少一个硬件处理器来计算医学图像的多个斑块中的每一个的斑块特征分数，计算医学图像的多个区域中的每一个的形状独特性得分，以及计算医学图像的显着图，通过结合补丁特征得分和形状独特性得分。

2. 发明申请

US20160188952A1 AUTOMATIC IMAGE CLASSIFICATION 有权
标题翻译：自动图像分类
公开(公告)号：US20160188952A1
公开(公告)日：2016-06-30
申请号：US14582216
申请日：2014-12-24
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Mattias Marder
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06K9/0055 , G06K9/4676 , G06K9/6228 , G06K9/6276 , G06K9/628 , G06K2009/4666 , G06K2209/25
摘要： A method, system and product for image classification. The method comprising obtaining a set of encoding functions and signature values which corresponds to a set of class images, wherein each pair of an encoding function and a signature value corresponds to a class image of the set of class images, wherein the signature value is a value produced by applying the encoding function on the class image; obtaining an image to be classified to a class associated with a class image of the set of class images; with respect to each class image of the set of class images: determining a transformation from the image to the class image; and applying the encoding function using the transformation on the image to produce a value; and automatically determining a class to which the image is classified based on the values and the signature values.
摘要翻译：一种用于图像分类的方法，系统和产品。该方法包括获得对应于一组类图像的一组编码函数和签名值，其中每对编码函数和签名值对应于该类图像集合的类图像，其中该签名值为通过对类图像应用编码函数产生的值; 获得要分类到与所述一组类图像的类图像相关联的类别的图像; 关于该类图像集合的每个类图像：确定从图像到类图像的变换; 以及使用所述图像上的变换来应用编码函数以产生一个值; 并且基于所述值和所述签名值自动确定所述图像被分类的类。

3. 发明申请

US20170046590A1 IMAGE FEATURE CLASSIFICATION 有权
标题翻译：图像特征分类
公开(公告)号：US20170046590A1
公开(公告)日：2017-02-16
申请号：US14824446
申请日：2015-08-12
申请人： International Business Machines Corporation
发明人： Sharon Alpert
IPC分类号： G06K9/46 , G06T11/60
CPC分类号： G06K9/4671 , G06K9/4623 , G06K9/4642 , G06K9/6247 , G06T11/60 , G06T2207/10081 , G06T2207/30068
摘要： A method, executed by one or more processors, includes computing a saliency surface for an image, conducting a mean shift algorithm on the saliency surface to provide mean shift data for the saliency surface, producing a mode voting map for the saliency surface from the mean shift data, and classifying features in the image according to the mode voting map. The features may correspond to medical conditions. In some embodiments, computing the saliency surface comprises determining a distinctiveness score for each of a plurality of image patches. In some embodiments, producing the mode voting map comprises determining a plurality of modes and an area of influence for each mode of the plurality of modes where the area of influence corresponds to mean shift data that leads to a particular mode. A corresponding computer program product and computer system are also disclosed herein.
摘要翻译：由一个或多个处理器执行的方法包括计算图像的显着表面，在显着表面上执行平均移位算法以提供显着表面的平均移位数据，从平均值产生显着表面的模式投票图根据模式投票图，移动数据和对图像中的特征进行分类。功能可能对应于医疗条件。在一些实施例中，计算显着表面包括确定多个图像块中的每一个的独特性得分。在一些实施例中，产生模式投票图包括确定多个模式的多个模式和影响区域，其中影响区域对应于导致特定模式的平均移位数据。本文还公开了相应的计算机程序产品和计算机系统。

4. 发明授权

US10706575B2 Unsupervised asymmetry detection 有权
公开(公告)号：US10706575B2
公开(公告)日：2020-07-07
申请号：US15832994
申请日：2017-12-06
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Miri Erihov , Pavel Kisilev
IPC分类号： G06T7/68 , G06T7/00 , G06K9/62 , G06T7/254 , G06T7/90
摘要： Asymmetries are detected in one or more images by partitioning each image to create a set of patches. Salient patches are identified, and an independent displacement for each patch is identified. The techniques used to identify the salient patches and the displacement for each patch are combined in a function to generate a score for each patch. The scores can be used to identify possible asymmetries.

5. 发明申请

US20170069113A1 UNSUPERVISED ASYMMETRY DETECTION 有权
标题翻译：非对称不对称检测
公开(公告)号：US20170069113A1
公开(公告)日：2017-03-09
申请号：US14845384
申请日：2015-09-04
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Miri Erihov , Pavel Kisilev
IPC分类号： G06T7/60 , G06T7/20 , G06T7/40 , G06T7/00
CPC分类号： G06T7/68 , G06K9/6203 , G06K9/6206 , G06K9/6215 , G06T7/0012 , G06T7/254 , G06T7/90 , G06T2207/10024 , G06T2207/10072 , G06T2207/20021 , G06T2207/30096
摘要： Asymmetries are detected in one or more images by partitioning each image to create a set of patches. Salient patches are identified, and an independent displacement for each patch is identified. The techniques used to identify the salient patches and the displacement for each patch are combined in a function to generate a score for each patch. The scores can be used to identify possible asymmetries.
摘要翻译：通过分割每个图像以创建一组补丁，在一个或多个图像中检测不对称。识别突出的贴片，并且识别每个贴片的独立位移。用于识别每个贴片的突出贴片和位移的技术被组合在一个函数中以产生每个贴片的得分。分数可用于识别可能的不对称性。

6. 发明授权

US09940731B2 Unsupervised asymmetry detection 有权
公开(公告)号：US09940731B2
公开(公告)日：2018-04-10
申请号：US14845384
申请日：2015-09-04
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Miri Erihov , Pavel Kisilev
IPC分类号： G06K9/00 , G06T7/60 , G06T7/00 , G06T7/20 , G06T7/40
CPC分类号： G06T7/68 , G06K9/6203 , G06K9/6206 , G06K9/6215 , G06T7/0012 , G06T7/254 , G06T7/90 , G06T2207/10024 , G06T2207/10072 , G06T2207/20021 , G06T2207/30096
摘要： Asymmetries are detected in one or more images by partitioning each image to create a set of patches. Salient patches are identified, and an independent displacement for each patch is identified. The techniques used to identify the salient patches and the displacement for each patch are combined in a function to generate a score for each patch. The scores can be used to identify possible asymmetries.

7. 发明申请

US20180096492A1 UNSUPERVISED ASYMMETRY DETECTION 审中-公开
公开(公告)号：US20180096492A1
公开(公告)日：2018-04-05
申请号：US15832994
申请日：2017-12-06
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Miri Erihov , Pavel Kisilev
IPC分类号： G06T7/00
摘要： Asymmetries are detected in one or more images by partitioning each image to create a set of patches. Salient patches are identified, and an independent displacement for each patch is identified. The techniques used to identify the salient patches and the displacement for each patch are combined in a function to generate a score for each patch. The scores can be used to identify possible asymmetries.

8. 发明授权

US09811905B2 Anomaly detection in medical imagery 有权
公开(公告)号：US09811905B2
公开(公告)日：2017-11-07
申请号：US15427073
申请日：2017-02-08
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Pavel Kisilev
IPC分类号： G06K9/00 , G06T7/00 , G06T5/40 , G06T7/13 , G06K9/46 , G06K9/62
CPC分类号： G06K9/4671 , G06K9/4628 , G06K9/4642 , G06K9/481 , G06K9/6267 , G06T5/40 , G06T7/0012 , G06T7/13 , G06T2207/10088 , G06T2207/10116 , G06T2207/30068 , G06T2207/30096
摘要： A method comprising using at least one hardware processor for computing a patch distinctiveness score for each of multiple patches of a medical image, computing a shape distinctiveness score for each of multiple regions of the medical image, and computing a saliency map of the medical image, by combining the patch distinctiveness score and the shape distinctiveness score.

9. 发明授权

US09704059B2 Anomaly detection in medical imagery 有权
公开(公告)号：US09704059B2
公开(公告)日：2017-07-11
申请号：US14178313
申请日：2014-02-12
申请人： International Business Machines Corporation
发明人： Sharon Alpert , Pavel Kisilev
IPC分类号： G06K9/00 , G06K9/46 , G06T7/00 , G06K9/48
CPC分类号： G06K9/4671 , G06K9/4628 , G06K9/4642 , G06K9/481 , G06K9/6267 , G06T5/40 , G06T7/0012 , G06T7/13 , G06T2207/10088 , G06T2207/10116 , G06T2207/30068 , G06T2207/30096
摘要： A method comprising using at least one hardware processor for computing a patch distinctiveness score for each of multiple patches of a medical image, computing a shape distinctiveness score for each of multiple regions of the medical image, and computing a saliency map of the medical image, by combining the patch distinctiveness score and the shape distinctiveness score.

10. 发明授权

US09679219B2 Image feature classification 有权
公开(公告)号：US09679219B2
公开(公告)日：2017-06-13
申请号：US14824446
申请日：2015-08-12
申请人： International Business Machines Corporation
发明人： Sharon Alpert
IPC分类号： G06K9/46 , G06T11/60
CPC分类号： G06K9/4671 , G06K9/4623 , G06K9/4642 , G06K9/6247 , G06T11/60 , G06T2207/10081 , G06T2207/30068
摘要： A method, executed by one or more processors, includes computing a saliency surface for an image, conducting a mean shift algorithm on the saliency surface to provide mean shift data for the saliency surface, producing a mode voting map for the saliency surface from the mean shift data, and classifying features in the image according to the mode voting map. The features may correspond to medical conditions. In some embodiments, computing the saliency surface comprises determining a distinctiveness score for each of a plurality of image patches. In some embodiments, producing the mode voting map comprises determining a plurality of modes and an area of influence for each mode of the plurality of modes where the area of influence corresponds to mean shift data that leads to a particular mode. A corresponding computer program product and computer system are also disclosed herein.

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