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1. 发明授权

US10176408B2 Systems and methods for analyzing pathologies utilizing quantitative imaging 有权
公开(公告)号：US10176408B2
公开(公告)日：2019-01-08
申请号：US14959732
申请日：2015-12-04
申请人： David S. Paik , Andrew J. Buckler , Kjell Johnson , Xiaonan Ma , Keith A. Moulton
发明人： David S. Paik , Andrew J. Buckler , Kjell Johnson , Xiaonan Ma , Keith A. Moulton
IPC分类号： G06K9/00 , G06K9/62
摘要： Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

2. 发明授权

US07346209B2 Three-dimensional pattern recognition method to detect shapes in medical images 有权
标题翻译：三维图案识别方法，用于检测医学图像中的形状
公开(公告)号：US07346209B2
公开(公告)日：2008-03-18
申请号：US10676839
申请日：2003-09-30
申请人： Salih B. Gokturk , Carlo Tomasi , Acar Burak , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
发明人： Salih B. Gokturk , Carlo Tomasi , Acar Burak , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
IPC分类号： G06K9/62
CPC分类号： G06K9/4609 , G06K9/4647 , G06K2209/05 , G06T7/0012 , G06T2207/30028
摘要： A detection and classification method of a shape in a medical image is provided. It is based on generating a plurality of 2-D sections through a 3-D volume in the medical image. In general, there are two steps. The first step is feature estimation to generate shape signatures for candidate volumes containing candidate shapes. The feature estimation method computes descriptors of objects or of their images. The second general step involves classification of these shape signatures for diagnosis. A classifier contains, builds and/or trains a database of descriptors for previously seen shapes, and then maps descriptors of novel images to categories corresponding to previously seen shapes or classes of shapes.
摘要翻译：提供了医疗图像中的形状的检测和分类方法。它基于在医学图像中通过3-D体积产生多个2-D部分。一般来说，有两个步骤。第一步是为包含候选形状的候选卷生成形状签名的特征估计。特征估计方法计算对象或其图像的描述符。第二个一般步骤包括对这些形状特征进行分类以进行诊断。分类器包含，构建和/或训练先前看到的形状的描述符数据库，然后将新颖图像的描述符映射到与以前看到的形状或类别形状对应的类别。

3. 发明授权

US07224827B2 Method for matching and registering medical image data 失效
标题翻译：用于匹配和注册医学图像数据的方法
公开(公告)号：US07224827B2
公开(公告)日：2007-05-29
申请号：US10673089
申请日：2003-09-26
申请人： Burak Acar , Christopher F. Beaulieu , David S. Paik , Sandy A. Napel , R. Brooke Jeffrey
发明人： Burak Acar , Christopher F. Beaulieu , David S. Paik , Sandy A. Napel , R. Brooke Jeffrey
IPC分类号： G06K9/00
CPC分类号： G06T3/40 , G06T7/33 , G06T7/38 , G06T2207/30028
摘要： An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine/prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and/or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.
摘要翻译：提供了一种用于登记倾斜和仰卧计算机断层摄影结肠镜数据的自动方法。该方法提高了放射科医师的整体解读效率，并为自动结合仰卧/俯卧式计算机辅助检测结果提供依据。该方法包括确定结肠的相对静止点（仰卧位和俯仰位置）匹配的冒号的（集中）路径或轴。仰卧位或倾斜路径的伸展和/或收缩都会执行这些点的注册。匹配和注册以迭代和递归的方式进行，并且基于一个或多个决策标准被认为是完成的。

4. 发明授权

US07729739B2 Heat diffusion based detection of structures of interest in medical images 失效
标题翻译：医学图像感兴趣结构的热扩散检测
公开(公告)号：US07729739B2
公开(公告)日：2010-06-01
申请号：US11000515
申请日：2004-11-29
申请人： Burak Acar , Ender Konukoglu , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
发明人： Burak Acar , Ender Konukoglu , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
IPC分类号： A61B6/00
CPC分类号： G06T7/0012 , G06T7/136 , G06T7/64 , G06T7/68 , G06T2207/20152 , G06T2207/30032
摘要： A method for detecting and identifying structures of interest such as colonic polyps or similar structures like lung nodules in volumetric (medical) images data is provided. The method includes obtaining a heat diffusion field (HDF) by applying a heat diffusion scheme to a volume of interest that includes structures. The obtained heat diffusion field is then used for identifying a structure of interest from the structures in the volume of interest using a geometrical analysis of the heat diffusion field. The heat diffusion scheme is, at least partly, governed by non-linear diffusion parameters. The identification includes two parts: (i) the computation of a spherical symmetry parameter, and (ii) the performance of a local analysis of the volume of interest and computation of a triangulization parameter.
摘要翻译：提供了一种用于在体积（医学）图像数据中检测和识别兴趣结构如结肠息肉或类似结节如肺结节的方法。该方法包括通过将热扩散方案应用到包括结构的感兴趣体积来获得热扩散场（HDF）。然后使用所述热扩散场的几何分析，将所获得的热扩散场用于从感兴趣体积中的结构中鉴定感兴趣的结构。热扩散方案至少部分地由非线性扩散参数控制。识别包括两部分：（i）球面对称参数的计算，以及（ii）感兴趣体积的局部分析和三角化参数的计算的性能。

5. 发明申请

US20080310693A1 Polyp Identification Through Subtraction of Models of Medical Images 失效
标题翻译：通过减少医学图像模型的多普勒识别
公开(公告)号：US20080310693A1
公开(公告)日：2008-12-18
申请号：US11666202
申请日：2005-11-08
申请人： David S. Paik , Padmavathi Sundaram , Christopher F. Beaulieu , Sandy A. Napel
发明人： David S. Paik , Padmavathi Sundaram , Christopher F. Beaulieu , Sandy A. Napel
IPC分类号： G06K9/00
CPC分类号： G06T19/00 , G06K9/00214 , G06T2210/41 , G16H50/50
摘要： A method of identifying polyps and in a medical image is provided. In a first step, a 3-dimensional model is made of the medical image that contains both polyps (if any were present in the original medical image) and folds. Next, a second 3-dimensional model of the medical image, which is a filtered version of the first model, is constructed in which folds are preserved, but polyps are minimized or eliminated. In a third step, any polyps that were contained in the medical image are identified by subtracting the second 3-dimensional model from the first 3-dimensional model. This subtraction results in a third 3-dimensional model, in which polyps are preserved but folds are minimized or eliminated. With the present inventive method, polyps may be easily and quickly identified without interference from folds.
摘要翻译：提供了一种识别息肉和医学图像的方法。在第一步中，三维模型由包含息肉（如果存在于原始医学图像中）和折叠的医学图像构成。接下来，构建作为第一模型的过滤版本的医学图像的第二三维模型，其中保留折叠，但是息肉被最小化或消除。在第三步骤中，通过从第一个3维模型中减去第二个三维模型来识别包含在医学图像中的任何息肉。该减法产生第三个三维模型，其中保留息肉，但折叠被最小化或消除。利用本发明的方法，可以容易且快速地识别息肉而不受折叠的干扰。

6. 发明授权

US5600932A Beam with enhanced bearing load strength and method of manufacture 失效
标题翻译：具有增强的轴承载荷强度和制造方法的梁
公开(公告)号：US5600932A
公开(公告)日：1997-02-11
申请号：US583338
申请日：1996-01-05
申请人： Young J. Paik , David S. Paik , Nelson S. Paik
发明人： Young J. Paik , David S. Paik , Nelson S. Paik
IPC分类号： E04C3/04 , E04C3/06 , E04C3/07
CPC分类号： E04C3/06 , E04C2003/0421 , E04C2003/0434 , E04C2003/0452 , Y10T29/49623 , Y10T29/49634 , Y10T29/49716
摘要： A first stage structural support beam (22,50) with flanges (12,14; 52,54) separated by an integral web (16) has the web stretched to increase the web height by a value .DELTA. following which a set of corrugations (34,48,62) is formed into the web. The resulting beam (38,40,50) has substantially increased weight-to-load characteristics as compared to the first stage beam.
摘要翻译：具有由整体腹板（16）分开的凸缘（12,14; 52,54）的第一级结构支撑梁（22,50）具有拉伸的腹板，以将腹板的高度增加一个值DELTA，随后将一组波纹 34,48,62）形成网。与第一级梁相比，所得到的梁（38,40,50）具有显着增加的重量 - 载荷特性。

7. 发明申请

US20170046839A1 SYSTEMS AND METHODS FOR ANALYZING PATHOLOGIES UTILIZING QUANTITATIVE IMAGING 审中-公开
标题翻译：使用定量成像分析病理学的系统和方法
公开(公告)号：US20170046839A1
公开(公告)日：2017-02-16
申请号：US14959732
申请日：2015-12-04
申请人： David S. Paik , Andrew J. Buckler , Kjell Johnson , Xiaonan Ma , Keith A. Moulton
发明人： David S. Paik , Andrew J. Buckler , Kjell Johnson , Xiaonan Ma , Keith A. Moulton
IPC分类号： G06T7/00
CPC分类号： G06K9/6296 , A61B6/032 , A61B6/504 , G06K9/00147
摘要： Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.
摘要翻译：本文介绍了利用定量成像分析病变的系统和方法。有利地，本公开的系统和方法利用分层分析框架，其从成像数据识别和定量生物学特性/分析物，然后基于量化的生物学特性/分析物来鉴定和表征一种或多种病理学。使用成像检查潜在生物学作为评估病理学的中介的这种分层方法提供了许多分析和处理优势，其优于被配置为直接确定和表征基础成像数据的病理学的系统和方法。

8. 发明申请

US20170046484A1 METHODS AND SYSTEMS FOR REPRESENTING, STORING, AND ACCESSING COMPUTABLE MEDICAL IMAGING-DERIVED QUANTITIES 审中-公开
标题翻译：用于表示，存储和访问可计算的医学成像衍生数量的方法和系统
公开(公告)号：US20170046484A1
公开(公告)日：2017-02-16
申请号：US15237249
申请日：2016-08-15
申请人： Andrew J. Buckler , Keith A. Moulton , Mary Buckler , Larry Martell , David S. Paik , Xiaonan Ma , Samantha St. Pierre
发明人： Andrew J. Buckler , Keith A. Moulton , Mary Buckler , Larry Martell , David S. Paik , Xiaonan Ma , Samantha St. Pierre
IPC分类号： G06F19/00 , G06F17/30 , G06F21/62
摘要： Methods and systems for making image-derived information available by performing analyses with semantic annotations accessible using semantic web technology for personalized medicine and discovery science are disclosed. Individual cases are identified according to an identification scheme. Targets for image analysis for each case are characterized in order to support tracking of a given anatomy, suspected pathology, confirmed pathology, or medical intervention at one or more timepoints. Access information to one or more medical images of each target at each one of the one or more timepoints is provided and stored. One or more levels of image-derived analysis is obtained and stored, the image derived analysis including at least one of imaging features, measured quantities, phenotypic descriptions, or predictions relative to said one case. A semantic search ability accesses across stored data items, for imaging or non-imaging associated data, according to concepts in an ontology according to relationships, without requiring the queries to be defined beforehand. By accessing predetermined data services, queries from the knowledge base are formed in order to collect data sets. The data sets can be used to test a hypothesis, the hypothesis related to supporting tracking of the given anatomy, the suspected pathology, the confirmed pathology, or the medical intervention.
摘要翻译：公开了通过使用可用于个性化医学和发现科学的语义网技术访问的语义注释进行分析来制作图像衍生信息的方法和系统。根据识别方案识别个案。每个病例的图像分析目标的特征在于支持在一个或多个时间点跟踪给定的解剖结构，疑似病理学，确认的病理学或医学干预。提供并存储在一个或多个时间点中的每一个处访问每个目标的一个或多个医学图像的信息。获得并存储图像衍生分析的一个或多个级别，所述图像衍生分析包括相对于所述一种情况的成像特征，测量量，表型描述或预测中的至少一种。根据关系，根据本体的概念，语义搜索能力跨存储的数据项访问，用于成像或非成像相关联的数据，而不需要事先定义查询。通过访问预定的数据服务，形成来自知识库的查询以便收集数据集。数据集可用于测试假设，与支持跟踪给定解剖结构相关的假设，可疑病理学，确诊病理学或医学干预。

9. 发明授权

US07272251B2 Method for detecting and classifying a structure of interest in medical images 失效
标题翻译：用于检测和分类医学图像中感兴趣的结构的方法
公开(公告)号：US07272251B2
公开(公告)日：2007-09-18
申请号：US10676721
申请日：2003-09-30
申请人： Burak Acar , Christopher F. Beaulieu , Salih B. Gokturk , Carlo Tomasi , David S. Paik , R. Brooke Jeffrey, Jr. , Sandy A. Napel
发明人： Burak Acar , Christopher F. Beaulieu , Salih B. Gokturk , Carlo Tomasi , David S. Paik , R. Brooke Jeffrey, Jr. , Sandy A. Napel
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06K9/00201 , G06T2207/30028 , G06T2207/30061
摘要： A method to detect and classify a structure of interest in a medical image is provided to enable high specificity without sacrificing the sensitivity of detection. The method is based on representing changes in three-dimensional image data with a vector field, characterizing the topology of this vector field and using the characterized topology of the vector field for classification of a structure of interest. The method could be used as a stand-alone method or as a post-processing method to enhance and classify outputs of a high-sensitivity low-specificity method to eliminate false positives.
摘要翻译：提供了一种用于检测和分类医学图像中感兴趣的结构的方法，以实现高特异性而不牺牲检测的灵敏度。该方法基于用矢量场表示三维图像数据的变化，表征该矢量场的拓扑，并且使用矢量场的表征拓扑来分类感兴趣的结构。该方法可用作独立方法或作为后处理方法来增强和分类高灵敏度低特异性方法的输出以消除假阳性。

10. 发明授权

US07043064B2 Method for characterizing shapes in medical images 失效
公开(公告)号：US07043064B2
公开(公告)日：2006-05-09
申请号：US10138113
申请日：2002-05-03
申请人： David S. Paik , Sandy A. Napel , Geoffrey D. Rubin , Christopher F. Beaulieu
发明人： David S. Paik , Sandy A. Napel , Geoffrey D. Rubin , Christopher F. Beaulieu
IPC分类号： G06K9/00
CPC分类号： G06K9/48 , G06K2209/053 , G06T7/0012 , Y10S128/922
摘要： A computer-implemented method for determining and characterizing, which portions or shapes of a medical image correspond to a shape of interest is provided. A candidate shape is obtained after which a visible surface is computed adjacent to this candidate shape. A visible surface includes one or more portions of the medical image that are visible by the candidate shape. Once the visible surface is determined, parameters of the visible surface are computed. Then the method further includes the step of determining whether the candidate shape corresponds to a shape of interest. The method further includes the step of computing features of the candidate shape and/or classifying the candidate shape. The advantage of the computer-implemented method is that it provides a high detection specificity, i.e. reducing false positives, without sacrificing sensitivity of the detection of a shape of interest.

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