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11. 发明授权

US07602965B2 Object detection using cross-section analysis 失效
标题翻译：使用横截面分析的对象检测
公开(公告)号：US07602965B2
公开(公告)日：2009-10-13
申请号：US11256471
申请日：2005-10-21
申请人： Lin Hong , Hong Shen , Shuping Qing
发明人： Lin Hong , Hong Shen , Shuping Qing
IPC分类号： G06K9/00
CPC分类号： G06K9/00201 , G06T7/0012
摘要： In a method of 3-D object detection, an image is pre-processed. Using cross-section analysis, a confidence array is built. A plurality of peaks in the confidence array are detected, wherein the peaks signify a likelihood of a 3-D object of interest.
摘要翻译：在三维物体检测的方法中，图像被预处理。使用横截面分析，构建置信阵列。检测置信阵列中的多个峰，其中峰表示感兴趣的3-D物体的可能性。

12. 发明授权

US07555152B2 System and method for detecting ground glass nodules in medical images 有权
标题翻译：用于检测医学图像中玻璃结节的系统和方法
公开(公告)号：US07555152B2
公开(公告)日：2009-06-30
申请号：US11324503
申请日：2006-01-03
申请人： Lin Hong , Yumao Lu , Hong Shen
发明人： Lin Hong , Yumao Lu , Hong Shen
IPC分类号： G06K9/00 , A61K39/00
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/10081 , G06T2207/30064
摘要： Detecting ground glass nodules in medical images includes calculating a probability distribution function of background lung tissue in a chest image, estimating a variation range of the background tissue probability distribution function, estimating a probability distribution function of an image point belonging to a ground glass nodule from the variation range of the background tissue probability distribution function by using a function corresponding to the variation range of the background tissue probability distribution function, and calculating a log likelihood function of the image from the background tissue probability distribution function and the estimated ground glass nodule probability distribution function, wherein the log likelihood function represents the confidence that a point in the image is not part of a ground glass nodule. The log likelihood function value for each point is compared to a confidence value of the background tissue, to determine if the point is a candidate ground glass nodule location.
摘要翻译：在医学图像中检测磨玻璃结节包括计算胸部图像中背景肺组织的概率分布函数，估计背景组织概率分布函数的变化范围，估计属于研磨玻璃结节的图像点的概率分布函数，通过使用与背景组织概率分布函数的变化范围相对应的函数来计算背景组织概率分布函数的变化范围，以及从背景组织概率分布函数和估计的研磨玻璃结节概率计算图像的对数似然函数分布函数，其中对数似然函数表示图像中的点不是研磨玻璃结节的一部分的置信度。将每个点的对数似然函数值与背景组织的置信度值进行比较，以确定该点是否为候选研磨玻璃结节位置。

13. 发明申请

US20090103797A1 Method and system for nodule feature extraction using background contextual information in chest x-ray images 有权
标题翻译：使用胸部x射线图像中的背景情境信息进行结节特征提取的方法和系统
公开(公告)号：US20090103797A1
公开(公告)日：2009-04-23
申请号：US12286968
申请日：2008-10-03
申请人： Lin Hong , Hong Shen
发明人： Lin Hong , Hong Shen
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06K2009/00932 , G06K2209/051 , G06K2209/053 , G06T2207/10116 , G06T2207/30064 , Y10S378/901
摘要： A method and system for nodule feature extract using background contextual information in chest x-ray images is disclosed. In order to detect false positives in nodule candidates for a chest x-ray image, background contextual information, such as contextual vessel tree information, is defined in the chest x-ray image. Features are extracted for each nodule candidate based on the background contextual information, and the extracted features are used to detect whether each nodule candidate is a false positive or a genuine nodule.
摘要翻译：公开了使用胸部X射线图像中的背景背景信息的结节特征提取的方法和系统。为了检测胸部x射线图像的结节候选物中的假阳性，在胸部x射线图像中定义了背景上下文信息，例如上下文血管树信息。基于背景上下文信息为每个结节候选提取特征，并且提取的特征用于检测每个结节候选物是假阳性还是真正的结节。

14. 发明申请

US20080285830A1 Computer Aided Lesion Assessment in Dynamic Contrast Enhanced Breast MRI Images 有权
标题翻译：动态对比增强乳腺MRI图像的计算机辅助病变评估
公开(公告)号：US20080285830A1
公开(公告)日：2008-11-20
申请号：US12117155
申请日：2008-05-08
申请人： Lin Hong , Hong Shen , Shuping Qing
发明人： Lin Hong , Hong Shen , Shuping Qing
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T2207/10096 , G06T2207/30096
摘要： A method for performing computer-assisted lesion assessment includes acquiring contrast enhanced MRI data. A region of interest is identified. Kinetic properties, morphological properties and pattern of enhancement are determined for the identified region of interest. A score is calculated for each of the kinetic properties, morphological properties, pattern of enhancement. A cumulative score is calculated for the identified region of interest. The scores are provided to a medical practitioner to assist in diagnosing the identified region of interest.
摘要翻译：用于执行计算机辅助病变评估的方法包括获取对比度增强的MRI数据。确定感兴趣的区域。确定感兴趣区域的动力学性质，形态特征和增强模式。计算每个动力学性质，形态特征，增强模式的得分。计算所识别的感兴趣区域的累积分数。分数被提供给医生以帮助诊断所识别的感兴趣的区域。

15. 发明授权

US08107699B2 Feature processing for lung nodules in computer assisted diagnosis 有权
标题翻译：计算机辅助诊断肺结节特征处理
公开(公告)号：US08107699B2
公开(公告)日：2012-01-31
申请号：US12170639
申请日：2008-07-10
申请人： Lin Hong , Christopher V. Alvino , Hong Shen
发明人： Lin Hong , Christopher V. Alvino , Hong Shen
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T2207/30061 , G06T2207/30064
摘要： Feature processing is provided for lung nodules in computer-assisted diagnosis. A feature that may better distinguish nodules from background is extracted using a Hough transform. Rather than relying on a specific boundary shape, the Hough transform accumulates evidence associated with a region, such as a ring region. The accumulated evidence provides a feature score without requiring a nodule to fit a specific shape. In another approach, a background level is determined from extracted features. Rather than attempting to normalize an image prior to extraction, the features are normalized. The feature normalization and generalized Hough transform extraction may be used together or alone.
摘要翻译：在计算机辅助诊断中为肺结节提供特征处理。使用霍夫变换提取可以更好地区分结节与背景的特征。霍夫变换不是依赖于特定的边界形状，而是累积与区域相关联的证据，例如环形区域。积累的证据提供了一个特征分数，而不需要结节来适应特定的形状。在另一种方法中，从提取的特征确定背景级别。在尝试在提取之前对图像进行归一化，而不是将特征归一化。特征归一化和广义霍夫变换提取可以一起使用或单独使用。

16. 发明授权

US08073214B2 Computer aided lesion assessment in dynamic contrast enhanced breast MRI images 有权
标题翻译：计算机辅助病变评估动态对比增强胸部MRI图像
公开(公告)号：US08073214B2
公开(公告)日：2011-12-06
申请号：US12117155
申请日：2008-05-08
申请人： Lin Hong , Hong Shen , Shuping Qing
发明人： Lin Hong , Hong Shen , Shuping Qing
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T2207/10096 , G06T2207/30096
摘要： A method for performing computer-assisted lesion assessment includes acquiring contrast enhanced MRI data. A region of interest is identified. Kinetic properties, morphological properties and pattern of enhancement are determined for the identified region of interest. A score is calculated for each of the kinetic properties, morphological properties, pattern of enhancement. A cumulative score is calculated for the identified region of interest. The scores are provided to a medical practitioner to assist in diagnosing the identified region of interest.
摘要翻译：用于执行计算机辅助病变评估的方法包括获取对比度增强的MRI数据。确定感兴趣的区域。确定感兴趣区域的动力学性质，形态特征和增强模式。计算每个动力学性质，形态特征，增强模式的得分。计算所识别的感兴趣区域的累积分数。分数被提供给医生以帮助诊断所识别的感兴趣的区域。

17. 发明申请

US20070081710A1 Systems and Methods For Segmenting Object Of Interest From Medical Image 有权
标题翻译：从医学图像分割兴趣对象的系统和方法
公开(公告)号：US20070081710A1
公开(公告)日：2007-04-12
申请号：US11537673
申请日：2006-10-02
申请人： Lin Hong , Hong Shen
发明人： Lin Hong , Hong Shen
IPC分类号： G06K9/00
CPC分类号： G06K9/38 , G06K2209/053 , G06T7/11 , G06T7/143 , G06T7/194 , G06T2207/10081 , G06T2207/20104 , G06T2207/30056 , G06T2207/30096
摘要： A system for segmenting a target organ tumor from an image includes a background model builder, a foreground model builder and a tumor region locator. The background model builder uses an intensity distribution estimate of voxels in an organ region in an image to build a background model. The foreground model builder uses an intensity distribution estimate of voxels in a target organ tumor to build a first foreground model. The tumor region locator uses the background model and the first foreground model to segment the target organ tumor to obtain a first segmentation result.
摘要翻译：用于从图像分割靶器官肿瘤的系统包括背景模型构建器，前景模型构建器和肿瘤区域定位器。背景模型构建器使用图像中器官区域中的体素的强度分布估计来构建背景模型。前景模型构建器使用目标器官肿瘤中的体素的强度分布估计来构建第一前景模型。肿瘤区域定位器使用背景模型和第一前景模型来分割目标器官肿瘤以获得第一分割结果。

18. 发明申请

US20060153451A1 System and method for detecting ground glass nodules in medical images 有权
公开(公告)号：US20060153451A1
公开(公告)日：2006-07-13
申请号：US11324503
申请日：2006-01-03
申请人： Lin Hong , Kumao Lu , Hong Shen
发明人： Lin Hong , Kumao Lu , Hong Shen
IPC分类号： G06K9/34
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/10081 , G06T2207/30064
摘要： Detecting ground glass nodules in medical images includes calculating a probability distribution function of background lung tissue in a chest image, estimating a variation range of the background tissue probability distribution function, estimating a probability distribution function of an image point belonging to a ground glass nodule from the variation range of the background tissue probability distribution function by using a function corresponding to the variation range of the background tissue probability distribution function, and calculating a log likelihood function of the image from the background tissue probability distribution function and the estimated ground glass nodule probability distribution function, wherein the log likelihood function represents the confidence that a point in the image is not part of a ground glass nodule. The log likelihood function value for each point is compared to a confidence value of the background tissue, to determine if the point is a candidate ground glass nodule location.

19. 发明授权

US07680314B2 Devices, systems, and methods for improving image consistency 失效
标题翻译：用于提高图像一致性的设备，系统和方法
公开(公告)号：US07680314B2
公开(公告)日：2010-03-16
申请号：US11539662
申请日：2006-10-09
申请人： Lin Hong
发明人： Lin Hong
IPC分类号： G06K9/00 , G06K9/34
CPC分类号： G06T7/143
摘要： Certain exemplary embodiments can comprise a method, which can comprise automatically rendering an improved image of a target object. The improved image obtained based upon a principal mode of the target object. The principal mode of the target object can be provided to an algorithm that is adapted to derive the improved image of the target object.
摘要翻译：某些示例性实施例可以包括一种方法，其可以包括自动呈现目标对象的改进的图像。基于目标对象的主要模式获得的改进的图像。可以将目标对象的主要模式提供给适于导出目标对象的改进图像的算法。

20. 发明申请

US20080112605A1 Methods and Apparatus for Automatic Body Part Identification and Localization 审中-公开
标题翻译：自动身体部位识别和定位的方法和装置
公开(公告)号：US20080112605A1
公开(公告)日：2008-05-15
申请号：US11933518
申请日：2007-11-01
申请人： Lin Hong , Shen Hong
发明人： Lin Hong , Shen Hong
IPC分类号： A61B5/00
CPC分类号： G06T7/74 , G06T2207/30004
摘要： Methods and apparatus are disclosed for automatically identifying and locating body parts in medical imaging. To automatically identify body parts of in an image, an identification and location algorithm is used. This establishes a reference frame in relation to the image. Then, a location of the head in relation to the frame is established. After upper and lower boundaries of the head are determined, a neck section of the image is identified. The neck section is identified using the lower boundary of the head section. The location of the neck section is then found. A thorax cage section is found and located positively below the neck section. The abdomen and pelvis are identified together and ultimately separately located and identified.
摘要翻译：公开了用于在医学成像中自动识别和定位身体部位的方法和装置。为了自动识别图像中的身体部位，使用识别和位置算法。这建立了与图像相关的参考帧。然后，建立头部相对于框架的位置。在确定头部的上边界和下边界之后，识别图像的颈部。使用头部的下边界识别颈部。然后找到颈部的位置。发现一个胸部保持架部分，并正确地位于颈部部分。腹部和骨盆被一起识别，最终分开定位和识别。

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