公开(公告)号：US20140023260A1

公开(公告)日：2014-01-23

申请号：US13666343

申请日：2012-11-01

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Yuchi Huang ,  Alberto Santamaria-Pang ,  Jens Rittscher

IPC: G06K9/34

CPC classification number: G06T7/155 ,  G06K9/0014 ,  G06K9/44 ,  G06T7/11 ,  G06T2207/10056 ,  G06T2207/20016 ,  G06T2207/20036 ,  G06T2207/20152 ,  G06T2207/30024

Abstract: Embodiments of the disclosure are directed to segmenting a digital image of biological tissue into biological units, such as cells. A first weak or data driven segmentation is generated using image data representing the digital image to segment the digital image into a first set of biological units. Applying a geometric model, each unit in the first set of biological units is ranked based on a similarity in shape and scale between the unit and one or more other units in the image. A subset of units from the first set of biological units is selected based on the rank of each biological unit relative to a predetermined threshold rank. A second weak or data driven segmentation may then be generated using image data including the subset of biological units to segment that portion of the digital image into a second set of biological units.

Abstract translation: 本公开的实施例涉及将生物组织的数字图像分割成诸如细胞的生物单元。 使用表示数字图像的图像数据来生成第一弱或数据驱动的分割，以将数字图像分割成第一组生物单元。 应用几何模型，基于图像中的单元和一个或多个其他单元之间的形状和尺度的相似性对第一组生物单元中的每个单元进行排序。 基于每个生物单元相对于预定阈值秩的等级来选择来自第一组生物单元的单元的子集。 然后可以使用包括生物单元的子集的图像数据来生成第二弱或数据驱动的分割，以将数字图像的该部分分割成第二组生物单元。

公开(公告)号：US09589360B2

公开(公告)日：2017-03-07

申请号：US13666343

申请日：2012-11-01

Applicant: General Electric Company

Inventor： Yuchi Huang ,  Alberto Santamaria-Pang ,  Jens Rittscher

IPC: G06K9/00 ,  G06T7/00 ,  G06K9/44

CPC classification number: G06T7/155 ,  G06K9/0014 ,  G06K9/44 ,  G06T7/11 ,  G06T2207/10056 ,  G06T2207/20016 ,  G06T2207/20036 ,  G06T2207/20152 ,  G06T2207/30024

Abstract: Embodiments of the disclosure are directed to segmenting a digital image of biological tissue into biological units, such as cells. A first weak or data driven segmentation is generated using image data representing the digital image to segment the digital image into a first set of biological units. Applying a geometric model, each unit in the first set of biological units is ranked based on a similarity in shape and scale between the unit and one or more other units in the image. A subset of units from the first set of biological units is selected based on the rank of each biological unit relative to a predetermined threshold rank. A second weak or data driven segmentation may then be generated using image data including the subset of biological units to segment that portion of the digital image into a second set of biological units.

Abstract translation: 本公开的实施例涉及将生物组织的数字图像分割成诸如细胞的生物单元。 使用表示数字图像的图像数据来生成第一弱或数据驱动的分割，以将数字图像分割成第一组生物单元。 应用几何模型，基于图像中的单元和一个或多个其他单元之间的形状和尺度的相似性对第一组生物单元中的每个单元进行排序。 基于每个生物单元相对于预定阈值秩的等级来选择来自第一组生物单元的单元的子集。 然后可以使用包括生物单元的子集的图像数据来生成第二弱或数据驱动的分割，以将数字图像的该部分分割成第二组生物单元。

公开(公告)号：US08908945B2

公开(公告)日：2014-12-09

申请号：US13657255

申请日：2012-10-22

Applicant: General Electric Company

Inventor： Alberto Santamaria-Pang ,  Yuchi Huang ,  Jens Rittscher

IPC: G06K9/00 ,  G06K9/34

CPC classification number: G06K9/34 ,  G06K9/00147 ,  G06T7/0012 ,  G06T7/12 ,  G06T2207/10056 ,  G06T2207/20016 ,  G06T2207/20036 ,  G06T2207/20072 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20152 ,  G06T2207/30024

Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.

Abstract translation: 分割生物组织的数字图像的方法包括访问由表示符合和不符合生物单元样本的形状的训练数据计算的排名模型。 排名模型可以包括在向量空间中定义超平面的支持向量。 该方法还包括访问表示数字图像的图像数据，识别数字图像中的第一形状和一组第二组成形状，其中第一形状包括该组第二组成形状的并集，确定第一数据的等级 将对应于该第二构成形状的图像数据中的第一形状的图像数据和第二数据点的等级指向矢量空间，并且使用第一形状或第二成分组合分割数字图像 基于哪个数据点具有更大的相应等级的形状。

公开(公告)号：US20140112557A1

公开(公告)日：2014-04-24

申请号：US13657255

申请日：2012-10-22

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Alberto Santamaria-Pang ,  Yuchi Huang ,  Jens Rittscher

IPC: G06K9/34

CPC classification number: G06K9/34 ,  G06K9/00147 ,  G06T7/0012 ,  G06T7/12 ,  G06T2207/10056 ,  G06T2207/20016 ,  G06T2207/20036 ,  G06T2207/20072 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20152 ,  G06T2207/30024

Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.

Abstract translation: 分割生物组织的数字图像的方法包括访问由表示符合和不符合生物单元样本的形状的训练数据计算的排名模型。 排名模型可以包括在向量空间中定义超平面的支持向量。 该方法还包括访问表示数字图像的图像数据，识别数字图像中的第一形状和一组第二组成形状，其中第一形状包括该组第二组成形状的并集，确定第一数据的等级 将与第一形状相对应的图像数据和对应于该组第二构成形状的图像数据中的第二数据点的等级排列成向量空间，并且使用第一形状或一组第二成分分割数字图像 基于哪个数据点具有更大的相应等级的形状。