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1. 发明授权

US07849024B2 Imaging system for producing recipes using an integrated human-computer interface (HCI) for image recognition, and learning algorithms 有权
标题翻译：用于使用用于图像识别的集成人机界面（HCI）和学习算法来生成食谱的成像系统
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。

2. 发明申请

US20080044084A1 Integrated human-computer interface for image recognition 有权
标题翻译：集成人机界面，用于图像识别
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。

3. 发明授权

US09123120B2 Progressive decision for cellular process selection 有权
标题翻译：细胞过程选择的进步决定
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。

4. 发明申请

US20140056504A1 Progressive decision for cellular process selection 有权
标题翻译：细胞过程选择的进步决定
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。

5. 发明申请

US20110274339A1 Method for kinetic characterization from temporal image sequence 审中-公开
标题翻译：从时间图像序列的动力学表征方法
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。

6. 发明申请

US20080120077A1 Method for kinetic characterization from temporal image sequence 审中-公开
标题翻译：从时间图像序列的动力学表征方法
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。

7. 发明申请

US20130322741A1 Teachable pattern scoring method 有权
公开(公告)号：US20130322741A1
公开(公告)日：2013-12-05
申请号：US13507115
申请日：2012-06-05
申请人： Shih-Jong J. Lee , Chi-Chou Huang
发明人： Shih-Jong J. Lee , Chi-Chou Huang
IPC分类号： G06K9/62
CPC分类号： G06K9/6256 , G06K9/0014 , G06K9/00147 , G06K9/62 , G06K9/6272
摘要： A computerized teachable pattern scoring method receives a teaching image and region pattern labels. A region segmentation is performed using the teaching image to generate regions of interest output. A feature measurement is performed using the teaching image and the regions of interest to generate region features output. A pattern score learning is performed using the region features and the region pattern labels to generate pattern score recipe output. A computerized region classification method using the region features and the pattern score recipe to generate pattern scores output. A region classification is performed using the pattern scores and region features to generate region class output.

8. 发明授权

US07031529B2 Method for detection optimization in image-based decision systems 有权
公开(公告)号：US07031529B2
公开(公告)日：2006-04-18
申请号：US10178166
申请日：2002-06-24
申请人： Shih-Jong J. Lee , Chi-Chou Huang , Seho Oh
发明人： Shih-Jong J. Lee , Chi-Chou Huang , Seho Oh
IPC分类号： G06K9/68
CPC分类号： G06K9/469 , G06T7/0002 , G06T7/62 , G06T7/66 , G06T2207/30164
摘要： A systematic way of linking structure constraints of components of a common object and checking and resolving their inconsistency is used to improve detection results in image-based decision systems. A multilevel Chain-And-Tree (CAT) model is used to direct processing using both forward and backward scans through the related components. Since components occur as parts of an object, the context (relational structure) in which the component appears can be used to reduce noise and variation affects. In the method, object knowledge is translated into constraints between components. The constraints are used to enhance feature detection, defect detection, and measurement accuracy and consistency.

9. 发明授权

US06507675B1 Structure-guided automatic learning for image feature enhancement 有权
标题翻译：结构引导自动学习图像特征增强
公开(公告)号：US06507675B1
公开(公告)日：2003-01-14
申请号：US09815466
申请日：2001-03-23
申请人： Shih-Jong J. Lee , Seho Oh , Chi-Chou Huang
发明人： Shih-Jong J. Lee , Seho Oh , Chi-Chou Huang
IPC分类号： G06K940
CPC分类号： G06K9/00127 , G06K9/4604 , G06T5/002 , G06T5/30 , G06T2207/20081
摘要： A structure-guided automatic learning system for image feature enhancement uses a learning image together with an application domain structure and detection target specification to produce a feature enhancement image processing recipe. An enhancement goodness measure is used to select between alternatives in the learning process. The feature enhancement recipe is used in an application module to process input images and produce a feature enhanced image output. Calipers are used for application domain structure and detection target specification. To unify the processing steps for all caliper specifications, a non-directional box caliper defined region such as a circle caliper or an arc caliper or other connected structures can be converted into a directional box caliper defined region so that a directional box caliper based feature enhancement method can be applied. The process can be inverted to convert a converted directional box caliper region back to the original format.
摘要翻译：用于图像特征增强的结构引导自动学习系统使用学习图像以及应用领域结构和检测目标规范来产生特征增强图像处理配方。增强善良度量被用于在学习过程中选择替代方案。特征增强配方在应用模块中用于处理输入图像并产生特征增强图像输出。卡尺用于应用领域结构和检测目标规范。为了统一所有卡尺规格的加工步骤，可以将诸如圆形卡尺或弧形卡尺或其他连接结构的非方向盒卡尺定义的区域转换成定向盒卡尺规定的区域，以便基于方向盒卡尺的特征增强方法可以应用。该过程可以反转，以将转换的方向盒卡尺区域转换回原始格式。

10. 发明授权

US09152884B2 Teachable pattern scoring method 有权
标题翻译：可教模式评分方法
公开(公告)号：US09152884B2
公开(公告)日：2015-10-06
申请号：US13507115
申请日：2012-06-05
申请人： Shih-Jong J. Lee , Chi-Chou Huang
发明人： Shih-Jong J. Lee , Chi-Chou Huang
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/6256 , G06K9/0014 , G06K9/00147 , G06K9/62 , G06K9/6272
摘要： A computerized teachable pattern scoring method receives a teaching image and region pattern labels. A region segmentation is performed using the teaching image to generate regions of interest output. A feature measurement is performed using the teaching image and the regions of interest to generate region features output. A pattern score learning is performed using the region features and the region pattern labels to generate pattern score recipe output. A computerized region classification method using the region features and the pattern score recipe to generate pattern scores output. A region classification is performed using the pattern scores and region features to generate region class output.
摘要翻译：计算机化教学模式评分方法接收教学图像和区域模式标签。使用教学图像执行区域分割以产生感兴趣的区域输出。使用教学图像和感兴趣区域来执行特征测量以产生区域特征输出。使用区域特征和区域图案标签来执行图案分数学习以生成图案分数配方输出。一种使用区域特征和模式分数配方的计算机化区域分类方法来生成模式分数输出。使用模式分数和区域特征来执行区域分类以产生区域类别输出。

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