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1. 发明申请

US20090092302A1 System and Method for Robust Segmentation of Pulmonary Nodules of Various Densities 有权
标题翻译：用于各种密度的肺结节的鲁棒分割的系统和方法
公开(公告)号：US20090092302A1
公开(公告)日：2009-04-09
申请号：US12243387
申请日：2008-10-01
申请人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
发明人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/187 , G06T2207/30064
摘要： A method for differentiating pulmonary nodules in digitized medical images includes identifying an object of interest from a digital image of the lungs, computing a first distance map of each point of the object of interest, determining a seed point from the first distance map, starting from the seed point, growing a first region by adding successive adjacent layers of points until a background point is reached, and partitioning the first region into a nodule region and a non-nodule region.
摘要翻译：用于区分数字化医学图像中的肺结节的方法包括从肺的数字图像识别感兴趣对象，计算感兴趣对象的每个点的第一距离图，从第一距离图确定种子点，从种子点，通过添加连续的相邻层点直到达到背景点来生长第一区域，并将第一区域划分成结节区域和非结节区域。

2. 发明授权

US08165369B2 System and method for robust segmentation of pulmonary nodules of various densities 有权
标题翻译：用于各种密度的肺结节的鲁棒分割的系统和方法
公开(公告)号：US08165369B2
公开(公告)日：2012-04-24
申请号：US12243387
申请日：2008-10-01
申请人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
发明人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/187 , G06T2207/30064
摘要： A method for differentiating pulmonary nodules in digitized medical images includes identifying an object of interest from a digital image of the lungs, computing a first distance map of each point of the object of interest, determining a seed point from the first distance map, starting from the seed point, growing a first region by adding successive adjacent layers of points until a background point is reached, and partitioning the first region into a nodule region and a non-nodule region.
摘要翻译：用于区分数字化医学图像中的肺结节的方法包括从肺的数字图像识别感兴趣对象，计算感兴趣对象的每个点的第一距离图，从第一距离图确定种子点，从种子点，通过添加连续的相邻层点直到达到背景点来生长第一区域，并将第一区域划分成结节区域和非结节区域。

3. 发明授权

US07756313B2 System and method for computer aided detection via asymmetric cascade of sparse linear classifiers 有权
标题翻译：通过稀疏线性分类器的不对称级联进行计算机辅助检测的系统和方法
公开(公告)号：US07756313B2
公开(公告)日：2010-07-13
申请号：US11592869
申请日：2006-11-03
申请人： Jinbo Bi , Senthil Periaswamy , Kazunori Okada , Toshiro Kubota , Glenn Fung , Marcos Salganicoff , R. Bharat Rao
发明人： Jinbo Bi , Senthil Periaswamy , Kazunori Okada , Toshiro Kubota , Glenn Fung , Marcos Salganicoff , R. Bharat Rao
IPC分类号： G06K9/00
CPC分类号： G06K9/6256 , G06K9/6282
摘要： A method for computer aided detection of anatomical abnormalities in medical images includes providing a plurality of abnormality candidates and features of said abnormality candidates, and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(wTx+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more complex features are used for each successive stage of said cascade of classifiers.
摘要翻译：一种用于计算机辅助检测医学图像中的解剖异常的方法，包括提供所述异常候选的多个异常候选和特征，并且使用形式符号的线性分类器（wTx）的分级级联将所述异常候选分类为真正的肯定或假阳性 + b），其中x是特征向量，w是加权向量，b是模型参数，其中使用不同权重来惩罚假否定和假阳性，并且其中对于级联的每个连续阶段使用更复杂的特征的分类器。

4. 发明申请

US20070110292A1 System and method for computer aided detection via asymmetric cascade of sparse linear classifiers 有权
标题翻译：通过稀疏线性分类器的不对称级联进行计算机辅助检测的系统和方法
公开(公告)号：US20070110292A1
公开(公告)日：2007-05-17
申请号：US11592869
申请日：2006-11-03
申请人： Jinbo Bi , Senthil Periaswamy , Kazunori Okada , Toshiro Kubota , Glenn Fung , Marcos Salganicoff , R. Rao
发明人： Jinbo Bi , Senthil Periaswamy , Kazunori Okada , Toshiro Kubota , Glenn Fung , Marcos Salganicoff , R. Rao
IPC分类号： G06K9/00
CPC分类号： G06K9/6256 , G06K9/6282
摘要： A method for computer aided detection of anatomical abnormalities in medical images includes providing a plurality of abnormality candidates and features of said abnormality candidates, and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(wTx+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more complex features are used for each successive stage of said cascade of classifiers.
摘要翻译：一种用于计算机辅助检测医学图像中的解剖异常的方法，包括提供所述异常候选的多个异常候选和特征，并且使用形式符号（w）的线性分类器的分级级联将所述异常候选分类为真阳性或假阳性 x + b），其中x是特征向量，w是加权向量，b是模型参数，其中不同的权重用于惩罚假否定和假肯定，并且其中更复杂的特征用于分级器级联的每个连续阶段。

5. 发明授权

US07876938B2 System and method for whole body landmark detection, segmentation and change quantification in digital images 有权
标题翻译：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
IPC分类号： G06K9/00 , G06K9/62
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。

6. 发明申请

US20070081712A1 System and method for whole body landmark detection, segmentation and change quantification in digital images 有权
标题翻译：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。

7. 发明授权

US07720271B2 Estimation of solitary pulmonary nodule diameters with reaction-diffusion segmentation 有权
标题翻译：用反应扩散分割估计孤立性肺结节直径
公开(公告)号：US07720271B2
公开(公告)日：2010-05-18
申请号：US11398100
申请日：2006-04-04
申请人： Toshiro Kubota
发明人： Toshiro Kubota
IPC分类号： G06K9/00
CPC分类号： G06K9/34 , G06K9/38 , G06T7/12 , G06T7/149 , G06T7/62 , G06T2207/10081 , G06T2207/20116 , G06T2207/30064
摘要： A reactive-diffusion method for estimating a diameter of an object of interest includes providing a volume of interest including a plurality of voxels, initializing at least two volumes of the volume of interest, wherein each of the voxels has at least two values corresponding to the at least two volumes of the volume of interest, respectively, performing a diffusion operation and a reaction operation on the voxels to adjust the at least two values, comparing, for each voxel, the at least two values to a threshold to assign each voxel to one of the at least two volumes, wherein the assignment of the voxels is a segmentation result, and estimating a diameter of the object of interest from the segmentation result, wherein the object of interest is represented by at least one of the at least two volumes but less than all the volumes.
摘要翻译：用于估计感兴趣对象的直径的反应性扩散方法包括提供包括多个体素的兴趣体积，初始化感兴趣体积的至少两个体积，其中每个体素具有对应于至少两个体积的感兴趣的体积分别对体素执行扩散操作和反应操作以调整至少两个值，将每个体素比较所述至少两个值到阈值以将每个体素分配到所述至少两个体积中的一个，其中所述体素的分配是分割结果，以及从所述分割结果估计所述感兴趣对象的直径，其中所述感兴趣对象由所述至少两个体积中的至少一个表示但少于所有卷。

8. 发明授权

US06201137B1 Process for purifying tetrahydrofurans used as starting material for polyether polyols 有权
标题翻译：纯化用作聚醚多元醇原料的四氢呋喃的方法
公开(公告)号：US06201137B1
公开(公告)日：2001-03-13
申请号：US09319031
申请日：1999-08-11
申请人： Hiroshi Nakaoka , Toshiro Kubota
发明人： Hiroshi Nakaoka , Toshiro Kubota
IPC分类号： C07D30706
CPC分类号： C07D307/08
摘要： Tetrahydrofurans suitable for use as starting materials in the synthesis of polyether polyols without causing coloration in the product polyether polyols can be obtained by contacting crude tetrahydrofurans with a mineral acid or a strongly acidic cation-exchange resin, followed by isolation through a simple distillation and/or rectification to obtain purified tetrahydrofurans.
摘要翻译：可以通过使粗四氢呋喃与无机酸或强酸性阳离子交换树脂接触，然后通过简单的蒸馏和/或反应产物分离来获得适合用作聚醚多元醇合成中的原料而不引起产物聚醚多元醇着色的四氢呋喃，或精馏以获得纯化的四氢呋喃。

9. 发明申请

US20060228014A1 Estimation of solitary pulmonary nodule diameters with reaction-diffusion segmentation 有权
标题翻译：用反应扩散分割估计孤立性肺结节直径
公开(公告)号：US20060228014A1
公开(公告)日：2006-10-12
申请号：US11398100
申请日：2006-04-04
申请人： Toshiro Kubota
发明人： Toshiro Kubota
IPC分类号： G06K9/00
CPC分类号： G06K9/34 , G06K9/38 , G06T7/12 , G06T7/149 , G06T7/62 , G06T2207/10081 , G06T2207/20116 , G06T2207/30064
摘要： A reactive-diffusion method for estimating a diameter of an object of interest includes providing a volume of interest including a plurality of voxels, initializing at least two volumes of the volume of interest, wherein each of the voxels has at least two values corresponding to the at least two volumes of the volume of interest, respectively, performing a diffusion operation and a reaction operation on the voxels to adjust the at least two values, comparing, for each voxel, the at least two values to a threshold to assign each voxel to one of the at least two volumes, wherein the assignment of the voxels is a segmentation result, and estimating a diameter of the object of interest from the segmentation result, wherein the object of interest is represented by at least one of the at least two volumes but less than all the volumes.
摘要翻译：用于估计感兴趣对象的直径的反应性扩散方法包括提供包括多个体素的兴趣体积，初始化感兴趣体积的至少两个体积，其中每个体素具有至少两个对应于至少两个体积的感兴趣的体积分别对体素执行扩散操作和反应操作以调整至少两个值，将每个体素比较所述至少两个值到阈值以将每个体素分配到所述至少两个体积中的一个，其中所述体素的分配是分割结果，以及从所述分割结果估计所述感兴趣对象的直径，其中所述感兴趣对象由所述至少两个体积中的至少一个表示但少于所有卷。

10. 发明申请

US20060228013A1 Estimation of solitary pulmonary nodule diameters with a hybrid segmentation approach 有权
公开(公告)号：US20060228013A1
公开(公告)日：2006-10-12
申请号：US11398099
申请日：2006-04-04
申请人： Toshiro Kubota , Kazunori Okada
发明人： Toshiro Kubota , Kazunori Okada
IPC分类号： G06K9/00
CPC分类号： G06K9/44 , G06K2209/053 , G06T7/0012 , G06T7/12 , G06T7/149 , G06T7/62 , G06T2207/10081 , G06T2207/20116 , G06T2207/30064 , Y10S378/901
摘要： A method for estimating a diameter of an object of interest, includes extracting a sub-volume of voxels around a marker identifying a location of the object of interest, and determining a segmentation result identifying an edge of the object of interest by a reactive-diffusion method. The method further includes performing a boundary check on the segmentation result to determine whether the object of interest is solitary, estimating a diameter of the object of interest from the segmentation result upon determining the object of interest to be solitary, and extracting the object of interest by performing ellipsoid fit on the sub-volume and estimating a diameter of the object of interest upon determining the object of interest to be non-solitary.

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