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1.发明申请METHOD, SYSTEM, SOFTWARE AND MEDIUM FOR ADVANCED INTELLIGENT IMAGE ANALYSIS AND DISPLAY OF MEDICAL IMAGES AND INFORMATION 有权方法，系统，软件和媒介用于高级智能图像分析和显示医学图像和信息公开(公告)号：US20120189176A1
公开(公告)日：2012-07-26
申请号：US13305495
申请日：2011-11-28
申请人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
发明人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
IPC分类号： G06K9/46
CPC分类号： G06T7/0016 , G06K9/6253 , G06T7/0012 , G06T7/40 , G06T7/62 , G06T11/003 , G06T15/08 , G06T15/20 , G06T17/00 , G06T19/20 , G06T2207/10076 , G06T2207/10084 , G06T2207/10088 , G06T2207/10116 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004 , G06T2207/30068
摘要： Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyses. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.
摘要翻译： 医学图像的计算机化解释用于定量分析多形态乳房图像，包括FFDM，2D / 3D超声，MRI或其他乳房成像方法的分析。 提供肿瘤和背景组织的实时表征，以及基于图像的生物标志物的计算，用于乳腺癌检测，诊断，预后，风险评估和治疗反应。 分析包括病变分割，以及基于病变或体素分析的相关特征（纹理/形态/动力特征）的提取。 提供了使用人工智能的几个分类任务中的特征组合。 根据1D，2D或3D分布的输出，其中相对于已知或未标记的情况下的计算来识别未知情况，可以通过维度降低技术。 输出到3D显示未知病例与已知或未标记病例的云的关系，其中云显示患有和没有疾病的患者群体的结构。
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2.发明授权Automated method and system for the detection of abnormalities in sonographic images 有权超声图像检测异常的自动化方法和系统公开(公告)号：US06855114B2
公开(公告)日：2005-02-15
申请号：US10126523
申请日：2002-04-22
CPC分类号： G06T7/0012 , A61B8/0825
摘要： A method of detecting a candidate abnormality in a sonographic medical image, based on determining a radial gradient index (RGI) at plural pixels, producing an RGI image, thresholding the RGI image, determining a candidate abnormality based on the thresholding step, and locating a center point of the candidate abnormality. The candidate abnormality may be classified by segmenting the candidate abnormality, including determining average radial gradients (ARDs) in the sonographic medical image based on the center point, extracting plural features from the segmented candidate abnormality, and determining a likelihood of the candidate abnormality being an actual abnormality based on the extracted plural features.
摘要翻译： 基于确定多个像素处的径向梯度指数（RGI），产生RGI图像，阈值化RGI图像，基于阈值步骤确定候选异常，以及定位一个检测超声医学图像中候选异常的方法 候选异常的中心点。 候选异常可以通过分割候选异常进行分类，包括基于中心点确定超声医学图像中的平均径向梯度（ARD），从分割的候选异常中提取多个特征，以及确定候选异常的可能性为 基于提取的多个特征的实际异常。
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3.发明授权Method, system, software and medium for advanced intelligent image analysis and display of medical images and information 有权方法，系统，软件和媒介，用于高级智能图像分析和医学图像和信息的显示公开(公告)号：US09536305B2
公开(公告)日：2017-01-03
申请号：US14887678
申请日：2015-10-20
申请人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
发明人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
IPC分类号： G06T7/00 , G06T11/00 , G06T15/08 , G06T15/20 , G06T17/00 , G06T19/20 , G06K9/62 , G06T7/60 , G06T7/40
CPC分类号： G06T7/0016 , G06K9/6253 , G06T7/0012 , G06T7/40 , G06T7/62 , G06T11/003 , G06T15/08 , G06T15/20 , G06T17/00 , G06T19/20 , G06T2207/10076 , G06T2207/10084 , G06T2207/10088 , G06T2207/10116 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004 , G06T2207/30068
摘要： Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyses. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.
摘要翻译： 医学图像的计算机化解释用于定量分析多形态乳房图像，包括FFDM，2D / 3D超声，MRI或其他乳房成像方法的分析。 提供肿瘤和背景组织的实时表征，以及基于图像的生物标志物的计算，用于乳腺癌检测，诊断，预后，风险评估和治疗反应。 分析包括病变分割，以及基于病变或体素分析的相关特征（纹理/形态/动力特征）的提取。 提供了使用人工智能的几个分类任务中的特征组合。 根据1D，2D或3D分布的输出，其中相对于已知或未标记的情况下的计算来识别未知情况，可以通过维度降低技术。 输出到3D显示未知病例与已知或未标记病例的云的关系，其中云显示患有和没有疾病的患者群体的结构。
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4.发明申请METHOD, SYSTEM, SOFTWARE AND MEDIUM FOR ADVANCED INTELLIGENT IMAGE ANALYSIS AND DISPLAY OF MEDICAL IMAGES AND INFORMATION 审中-公开方法，系统，软件和媒介用于高级智能图像分析和显示医学图像和信息公开(公告)号：US20160078624A1
公开(公告)日：2016-03-17
申请号：US14887678
申请日：2015-10-20
申请人： Maryellen L. GIGER , Robert TOMEK , Jeremy Bancroft BROWN , Andrew Robert JAMIESON , Li LAN , Michael R. CHINANDER , Karen DRUKKER , Hui Li , Neha BHOOSHAN , Gillian NEWSTEAD
发明人： Maryellen L. GIGER , Robert TOMEK , Jeremy Bancroft BROWN , Andrew Robert JAMIESON , Li LAN , Michael R. CHINANDER , Karen DRUKKER , Hui Li , Neha BHOOSHAN , Gillian NEWSTEAD
CPC分类号： G06T7/0016 , G06K9/6253 , G06T7/0012 , G06T7/40 , G06T7/62 , G06T11/003 , G06T15/08 , G06T15/20 , G06T17/00 , G06T19/20 , G06T2207/10076 , G06T2207/10084 , G06T2207/10088 , G06T2207/10116 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004 , G06T2207/30068
摘要： Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyses. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.
摘要翻译： 医学图像的计算机化解释用于定量分析多形态乳房图像，包括FFDM，2D / 3D超声，MRI或其他乳房成像方法的分析。 提供肿瘤和背景组织的实时表征，以及基于图像的生物标志物的计算，用于乳腺癌检测，诊断，预后，风险评估和治疗反应。 分析包括病变分割，以及基于病变或体素分析的相关特征（纹理/形态/动力特征）的提取。 提供了使用人工智能的几个分类任务中的特征组合。 根据1D，2D或3D分布的输出，其中相对于已知或未标记的情况下的计算来识别未知情况，可以通过维度降低技术。 输出到3D显示未知病例与已知或未标记病例的云的关系，其中云显示患有和没有疾病的患者群体的结构。
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5.发明授权Method, system, software and medium for advanced intelligent image analysis and display of medical images and information 有权方法，系统，软件和媒介，用于高级智能图像分析和医学图像和信息的显示公开(公告)号：US09208556B2
公开(公告)日：2015-12-08
申请号：US13305495
申请日：2011-11-28
申请人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
发明人： Maryellen L. Giger , Robert Tomek , Jeremy Bancroft Brown , Andrew Robert Jamieson , Li Lan , Michael R. Chinander , Karen Drukker , Hui Li , Neha Bhooshan , Gillian Newstead
CPC分类号： G06T7/0016 , G06K9/6253 , G06T7/0012 , G06T7/40 , G06T7/62 , G06T11/003 , G06T15/08 , G06T15/20 , G06T17/00 , G06T19/20 , G06T2207/10076 , G06T2207/10084 , G06T2207/10088 , G06T2207/10116 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004 , G06T2207/30068
摘要： Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyzes. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.
摘要翻译： 医学图像的计算机化解释用于定量分析多形态乳房图像，包括FFDM，2D / 3D超声，MRI或其他乳房成像方法的分析。 提供肿瘤和背景组织的实时表征，以及基于图像的生物标志物的计算，用于乳腺癌检测，诊断，预后，风险评估和治疗反应。 分析包括病变分割，以及基于病变或体素分析的相关特征（纹理/形态/动力特征）的提取。 提供了使用人工智能的几个分类任务中的特征组合。 根据1D，2D或3D分布的输出，其中相对于已知或未标记的情况下的计算来识别未知情况，可以通过维度降低技术。 输出到3D显示未知病例与已知或未标记病例的云的关系，其中云显示患有和没有疾病的患者群体的结构。
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