公开(公告)号：US20110274339A1

公开(公告)日：2011-11-10

申请号：US13135711

申请日：2011-07-13

申请人： Shih-Jong J. Lee ,  Seho Oh ,  Samuel V. Alworth

发明人： Shih-Jong J. Lee ,  Seho Oh ,  Samuel V. Alworth

IPC分类号： G06K9/00

CPC分类号： G06K9/00127 ,  G06K2009/3291

摘要： A computerized derivable kinetic characterization measurement method for live cell kinetic characterization inputs kinetic recognition data for a plurality of time frames. A single cell measurement step is performed using the kinetic recognition data for a plurality of time frames to generate single cell feature for a plurality of time frames output. The single cell feature includes cell morphological profiling feature. A kinetic measurement step uses the single cell feature for a plurality of time frames to generate kinetic feature output. A trajectory measurement step uses the single cell feature for a plurality of time frames and the kinetic feature to generate trajectory feature output. An interval measurement step uses the kinetic feature to generate interval feature output. A cell state classifier step uses the interval feature to generate cell state output. A state based measurement uses the single cell feature, the kinetic feature and the cell state to generate state based feature output.

摘要翻译： 用于活细胞动力学特征的计算机可推导动力学表征测量方法输入多个时间帧的动力学识别数据。 使用多个时间帧的动力学识别数据来执行单个小区测量步骤，以生成多个时间帧输出的单个小区特征。 单细胞特征包括细胞形态分析特征。 动力学测量步骤使用多个时间帧的单细胞特征来产生动力特征输出。 轨迹测量步骤使用单个小区特征用于多个时间帧，并且所述动力特征生成轨迹特征输出。 间隔测量步骤使用动力学特征来产生间隔特征输出。 单元状态分类器步骤使用间隔特征来生成单元格状态输出。 基于状态的测量使用单细胞特征，动力学特征和细胞状态来产生基于状态的特征输出。

公开(公告)号：US20080120077A1

公开(公告)日：2008-05-22

申请号：US11604590

申请日：2006-11-22

申请人： Shih-Jong J. Lee ,  Seho Oh ,  Yuhui Y.C. Cheng ,  Samuel V. Alworth

发明人： Shih-Jong J. Lee ,  Seho Oh ,  Yuhui Y.C. Cheng ,  Samuel V. Alworth

IPC分类号： G06G7/48

CPC分类号： G06K9/00127 ,  G06K2009/3291

摘要： A computerized derivable kinetic characterization measurement method for live cell kinetic characterization inputs kinetic recognition data for a plurality of time frames. A single cell measurement step is performed using the kinetic recognition data for a plurality of time frames to generate single cell feature for a plurality of time frames output. The single cell feature includes cell morphological profiling feature. A kinetic measurement step uses the single cell feature for a plurality of time frames to generate kinetic feature output. A trajectory measurement step uses the single cell feature for a plurality of time frames and the kinetic feature to generate trajectory feature output. An interval measurement step uses the kinetic feature to generate interval feature output. A cell state classifier step uses the interval feature to generate cell state output. A state based measurement uses the single cell feature, the kinetic feature and the cell state to generate state based feature output.

摘要翻译： 用于活细胞动力学特征的计算机可推导动力学表征测量方法输入多个时间帧的动力学识别数据。 使用多个时间帧的动力学识别数据来执行单个小区测量步骤，以生成多个时间帧输出的单个小区特征。 单细胞特征包括细胞形态分析特征。 动力学测量步骤使用多个时间帧的单细胞特征来产生动力特征输出。 轨迹测量步骤使用单个小区特征用于多个时间帧，并且所述动力特征生成轨迹特征输出。 间隔测量步骤使用动力学特征来产生间隔特征输出。 单元状态分类器步骤使用间隔特征来生成单元状态输出。 基于状态的测量使用单细胞特征，动力学特征和细胞状态来产生基于状态的特征输出。

公开(公告)号：US09123120B2

公开(公告)日：2015-09-01

申请号：US13573136

申请日：2012-08-24

申请人： Shih-Jong J. Lee ,  Samuel V. Alworth

发明人： Shih-Jong J. Lee ,  Samuel V. Alworth

IPC分类号： G06T7/00 ,  G01N33/50 ,  G06K9/00 ,  C12M1/34 ,  C12M1/36

CPC分类号： G06T7/0081 ,  C12M41/36 ,  C12M41/48 ,  G01N33/5005 ,  G06K9/00127 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/174 ,  G06T2207/30024

摘要： A computerized image guided biological cellular process progressive selection method receives at least one state cell image. A state cell region recognition is performed using the state cell image to generate state cell region output. A state cell measurement is performed using the state cell region to generate at least one state cell feature output. A state cell decision is performed using the state cell feature to generate state cell selection decision output. The selected cell is progressively selected in at least one follow-on states by its image guided state cell selection method. The method further includes at least one additional image acquired in a later frame of same state and state cell feature includes temporal features of growth patterns.

摘要翻译： 计算机图像引导的生物细胞过程逐行选择方法接收至少一个状态单元图像。 使用状态单元图像执行状态单元区域识别以生成状态单元区域输出。 使用状态单元区域执行状态单元测量以产生至少一个状态单元特征输出。 使用状态单元特征执行状态单元决定以产生状态单元选择决定输出。 所选择的单元通过其图像引导状态单元选择方法在至少一个后续状态中逐渐选择。 该方法还包括在相同状态和状态单元特征的后续帧中获取的至少一个附加图像包括增长模式的时间特征。

公开(公告)号：US20140056504A1

公开(公告)日：2014-02-27

申请号：US13573136

申请日：2012-08-24

申请人： Shih-Jong J. Lee ,  Samuel V. Alworth

发明人： Shih-Jong J. Lee ,  Samuel V. Alworth

IPC分类号： G06K9/00

CPC分类号： G06T7/0081 ,  C12M41/36 ,  C12M41/48 ,  G01N33/5005 ,  G06K9/00127 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/174 ,  G06T2207/30024

摘要： A computerized image guided biological cellular process progressive selection method receives at least one state cell image. A state cell region recognition is performed using the state cell image to generate state cell region output. A state cell measurement is performed using the state cell region to generate at least one state cell feature output. A state cell decision is performed using the state cell feature to generate state cell selection decision output. The selected cell is progressively selected in at least one follow-on states by its image guided state cell selection method. The method further includes at least one additional image acquired in a later frame of same state and state cell feature includes temporal features of growth patterns.

摘要翻译： 计算机图像引导的生物细胞过程逐行选择方法接收至少一个状态单元图像。 使用状态单元图像执行状态单元区域识别以生成状态单元区域输出。 使用状态单元区域执行状态单元测量以生成至少一个状态单元特征输出。 使用状态单元特征执行状态单元决定以产生状态单元选择决定输出。 所选择的单元通过其图像引导状态单元选择方法在至少一个后续状态中逐渐选择。 该方法还包括在相同状态和状态单元特征的后续帧中获取的至少一个附加图像包括增长模式的时间特征。

公开(公告)号：US07849024B2

公开(公告)日：2010-12-07

申请号：US11506081

申请日：2006-08-16

申请人： Shih-Jong J. Lee ,  Samuel V. Alworth ,  Tuan Phan ,  Chi Chou Huang ,  Christopher Birnbaum

发明人： Shih-Jong J. Lee ,  Samuel V. Alworth ,  Tuan Phan ,  Chi Chou Huang ,  Christopher Birnbaum

IPC分类号： G06F15/18

CPC分类号： G06T5/00 ,  G06T7/00 ,  G06T2200/24 ,  G06T2207/30004

摘要： A Recognition Frame presents multi-level application elements to the user simultaneously through a computer graphical user interface. The interface consists of an image display panel for displaying image channels; a data display panel for displaying object measurements and summary statistics; a configuration display panel for displaying recipe content; a master tab for selecting the panels. It also consists of a processing toolbar for context dependent processing tool display. The Recognition Frame further comprises a second side frame for data object display and charting. The second side frame has a tabular arrangement consisting of properties tab, controls tab, and charts tab. The Recognition Frame links application elements through a complex data model wherein interface display is automatically updated when one element is changed.

摘要翻译： 识别框架通过计算机图形用户界面同时向用户提供多层应用程序元素。 该接口包括用于显示图像通道的图像显示面板; 用于显示物体测量和总结统计数据的数据显示面板; 用于显示配方内容的配置显示面板; 用于选择面板的主选项卡。 它还包括用于上下文相关处理工具显示的处理工具栏。 识别框架还包括用于数据对象显示和制图的第二侧框架。 第二侧框架具有由属性选项卡，控件选项卡和图表选项卡组成的表格布置。 识别框架通过复杂数据模型来链接应用元素，其中当一个元素被改变时，自动更新界面显示。

公开(公告)号：US20080044084A1

公开(公告)日：2008-02-21

申请号：US11506081

申请日：2006-08-16

申请人： Shih-Jong J. Lee ,  Samuel V. Alworth ,  Tuan Phan ,  Chi Chou Huang ,  Christopher Birnbaum

发明人： Shih-Jong J. Lee ,  Samuel V. Alworth ,  Tuan Phan ,  Chi Chou Huang ,  Christopher Birnbaum

IPC分类号： G06K9/46

CPC分类号： G06T5/00 ,  G06T7/00 ,  G06T2200/24 ,  G06T2207/30004

摘要： A Recognition Frame presents multi-level application elements to the user simultaneously through a computer graphical user interface. The interface consists of an image display panel for displaying image channels; a data display panel for displaying object measurements and summary statistics; a configuration display panel for displaying recipe content; a master tab for selecting the panels. It also consists of a processing toolbar for context dependent processing tool display. The Recognition Frame further comprises a second side frame for data object display and charting. The second side frame has a tabular arrangement consisting of properties tab, controls tab, and charts tab. The Recognition Frame links application elements through a complex data model wherein interface display is automatically updated when one element is changed.

摘要翻译： 识别框架通过计算机图形用户界面同时向用户提供多层应用程序元素。 该接口包括用于显示图像通道的图像显示面板; 用于显示物体测量和总结统计数据的数据显示面板; 用于显示配方内容的配置显示面板; 用于选择面板的主选项卡。 它还包括用于上下文相关处理工具显示的处理工具栏。 识别框架还包括用于数据对象显示和制图的第二侧框架。 第二侧框架具有由属性选项卡，控件选项卡和图表选项卡组成的表格布置。 识别框架通过复杂数据模型来链接应用元素，其中当一个元素被改变时，自动更新界面显示。

公开(公告)号：US07263509B2

公开(公告)日：2007-08-28

申请号：US10411437

申请日：2003-04-09

申请人： Shih-Jong J. Lee ,  Seho Oh

发明人： Shih-Jong J. Lee ,  Seho Oh

IPC分类号： G06F12/00 ,  G06N5/02

CPC分类号： G06N5/04 ,  G06K9/342 ,  G06K9/4638 ,  G06N5/025 ,  G06N99/005

摘要： An intelligent spatial reasoning method receives a plurality of object sets. A spatial mapping feature learning method uses the plurality of object sets to create at least one salient spatial mapping feature output. It performs spatial reasoning rule learning using the at least one spatial mapping feature to create at least one spatial reasoning rule output. The spatial mapping feature learning method performs a spatial mapping feature set generation step followed by a feature learning step. The spatial mapping feature set is generated by repeated application of spatial correlation between two object sets. The feature learning method consists of a feature selection step and a feature transformation step and the spatial reasoning rule learning method uses the supervised learning method.The spatial reasoning approach of this invention automatically characterizes spatial relations of multiple sets of objects by comprehensive collections of spatial mapping features. Some of the features have clearly understandable physical, structural, or geometrical meanings. Others are statistical characterizations, which may not have clear physical, structural or geometrical meanings when considered individually. A combination of these features, however, could characterize subtle physical, structural or geometrical conditions under practical situations. One key advantage of this invention is the ability to characterize subtle differences numerically using a comprehensive feature set.

摘要翻译： 智能空间推理方法接收多个对象集。 空间映射特征学习方法使用多个对象集来创建至少一个显着的空间映射特征输出。 它使用至少一个空间映射特征来执行空间推理规则学习以创建至少一个空间推理规则输出。 空间映射特征学习方法执行空间映射特征集生成步骤，随后是特征学习步骤。 通过重复应用两个对象集之间的空间相关性来生成空间映射特征集。 特征学习方法由特征选择步骤和特征变换步骤组成，空间推理规则学习方法采用监督学习方法。 本发明的空间推理方法通过空间映射特征的综合集合自动表征多组对象的空间关系。 一些功能具有明确的理解，物理，结构或几何意义。 其他是统计特征，当单独考虑时可能没有明确的物理，结构或几何意义。 然而，这些特征的组合可以在实际情况下表征微妙的物理，结构或几何条件。 本发明的一个关键优点是能够使用综合特征集在数值上表征微妙的差异。

公开(公告)号：US07076093B2

公开(公告)日：2006-07-11

申请号：US10247723

申请日：2002-09-16

申请人： Shih-Jong J. Lee ,  Seho Oh

发明人： Shih-Jong J. Lee ,  Seho Oh

IPC分类号： G06K9/00

CPC分类号： G06T7/001 ,  G06T7/12 ,  G06T7/155 ,  G06T2207/20041

摘要： A structure-guided transformation transforms a region of an image into a region in the structure-transformed image according to the desired structure. The invention achieves efficient and accurate structure-guided processing such as filtering, detection and comparison in the transformed domain and thereby facilitates use of simple operations to enhance or detect straight lines or edges. Structure information is used to enhance and detect image features of interest even when the shape of the image structure is not regular. Both global and local structures of objects can be inspected. Global structure inspection detects gross errors in image structure; therefore side effects caused by mismatched structure-guided processing are avoided. Subtle defects along the edge of a structure can be detected by local structure inspection. Structure information guidance provides an edge detection inspection system that tolerates significant noise and contrast variations.

摘要翻译： 结构引导变换根据期望的结构将图像的区域变换为结构变换图像中的区域。 本发明实现了有效和准确的结构引导处理，如变换域中的过滤，检测和比较，从而便于使用简单的操作来增强或检测直线或边缘。 即使当图像结构的形状不规则时，结构信息也用于增强和检测感兴趣的图像特征。 可以检查对象的全局和局部结构。 全局结构检查检测图像结构中的粗略错误; 因此避免了由错配的结构引导处理引起的副作用。 沿结构边缘的微小缺陷可以通过局部结构检查来检测。 结构信息指导提供了边缘检测检测系统，其容忍显着的噪声和对比度变化。

公开(公告)号：US06842538B2

公开(公告)日：2005-01-11

申请号：US09815816

申请日：2001-03-23

申请人： Shih-Jong J. Lee ,  Seho Oh ,  Larry A. Nelson

发明人： Shih-Jong J. Lee ,  Seho Oh ,  Larry A. Nelson

IPC分类号： G06K9/46 ,  G06K9/00 ,  G06K9/36 ,  G06K9/62 ,  H04N1/00

CPC分类号： G06K9/4604

摘要： Mark detection and position determination are improved by use of directional elongated filters, symmetry, gray scale image processing, structural constraints, and learning. Directional elongated filters are used to pre-process images of registration marks to create masks and enhanced images. Working sequentially, portions of the mark are detected and classified. The input gray scale image of the mark is processed using its structural constraints in conjunction with a mask for the detected mark. A cost function estimation determines mark position and orientation with sub-pixel accuracy. Learning is used to improve specific application performance.

摘要翻译： 通过使用定向细长滤波器，对称性，灰度图像处理，结构约束和学习来提高标记检测和位置确定。 定向拉长过滤器用于预处理对准标记的图像以创建掩模和增强图像。 按顺序工作，对标记的部分进行检测和分类。 使用其结构约束结合用于检测标记的掩码来处理标记的输入灰度图像。 成本函数估计用子像素精度确定标记位置和方向。 学习用于提高特定的应用程序性能。

公开(公告)号：US06404934B1

公开(公告)日：2002-06-11

申请号：US09692948

申请日：2000-10-20

申请人： Shih-Jong J. Lee ,  Seho Oh

发明人： Shih-Jong J. Lee ,  Seho Oh

IPC分类号： G06T520

CPC分类号： G06T5/30

摘要： A high speed image processing apparatus is created through the use of cascaded elongated filters. The processing speed of the filters is kernel size insensitive, enabling use of general purpose computing facilities to process high resolution, monochrome, and multi-spectrum images. Elongated filters described include both linear and non-linear filters. Very large kernel and multi-dimensional image processing is accomplished with reduced complexity and portable programming instructions.

摘要翻译： 通过使用级联的细长过滤器创建高速图像处理装置。 过滤器的处理速度是内核大小不敏感的，可以使用通用计算机来处理高分辨率，单色和多光谱图像。 所描述的细长滤波器包括线性和非线性滤波器。 非常大的内核和多维图像处理通过降低的复杂性和便携式编程指令来实现。