公开(公告)号：US09123099B2

公开(公告)日：2015-09-01

申请号：US14153569

申请日：2014-01-13

Applicant: Wake Forest University Health Sciences

Inventor： William Gregory Hundley ,  Craig A. Hamilton ,  Ralph B. D'Agostino

IPC: G06K9/00 ,  G06T7/00 ,  A61B5/055 ,  A61B6/00 ,  G01R33/28 ,  A61B5/00 ,  G01R33/54

CPC classification number: G06T7/0012 ,  A61B5/0044 ,  A61B5/055 ,  A61B5/7285 ,  A61B6/466 ,  A61B6/503 ,  A61B6/504 ,  A61B6/506 ,  A61B6/541 ,  G01R33/283 ,  G01R33/546 ,  G06T2207/10088 ,  G06T2207/20104 ,  G06T2207/30048 ,  Y10S128/92 ,  Y10S128/921 ,  Y10S128/922 ,  Y10S128/923 ,  Y10S128/924

Abstract: Physician interactive workstations with global voxel distribution visualization may also include one or more of a 3-D color scale image of a population of voxel in target regions, organs or systems. The workstation may be configured to evaluate intensity or other measures of voxels of patient images associated with tissue for early detection of a global injury.

Abstract translation: 具有全局体素分布可视化的医师交互式工作站还可以包括目标区域，器官或系统中的体素群体的3-D色标图像中的一个或多个。 工作站可以被配置为评估与组织相关联的患者图像的体素的强度或其他度量，以用于早期检测全局损伤。

公开(公告)号：US08165671B2

公开(公告)日：2012-04-24

申请号：US11136327

申请日：2005-05-24

Applicant: Gary A. Freeman ,  James E. Brewer

Inventor： Gary A. Freeman ,  James E. Brewer

IPC: A61N1/39

CPC classification number: A61B5/7264 ,  A61B5/0464 ,  A61B5/7207 ,  A61B5/7257 ,  A61B5/726 ,  A61H31/005 ,  A61H2201/5015 ,  A61H2230/04 ,  A61N1/3925 ,  G06F19/00 ,  G09B23/288 ,  Y10S128/92 ,  Y10S128/923 ,  Y10S128/924 ,  Y10S706/924

Abstract: A method of automatically determining which type of treatment is most appropriate for (or the physiological state of) a patient. The method comprises transforming one or more time domain measurements from the patient into frequency domain data representative of the frequency content of the time domain measurements; processing the frequency domain data to form a plurality of spectral bands, the content of a spectral band representing the frequency content of the measurements within a frequency band; forming a weighted sum of the content of the spectral bands, with different weighting coefficients applied to at least some of the spectral bands; determining the type of treatment (or physiological state) based on the weighted sum.

Abstract translation: 一种自动确定哪种类型的治疗最适合患者的（或生理状态）的方法。 该方法包括将来自患者的一个或多个时域测量值转换为表示时域测量的频率内容的频域数据; 处理频域数据以形成多个频谱带，表示频带内的测量的频率内容的频谱带的内容; 形成对频谱带的内容的加权和，其中加权系数应用于至少一些频谱带; 基于加权和确定治疗类型（或生理状态）。

公开(公告)号：US08160357B2

公开(公告)日：2012-04-17

申请号：US12847372

申请日：2010-07-30

Applicant: Akinola Akinyemi ,  Ian Poole ,  Costas Plakas ,  Jim Piper

Inventor： Akinola Akinyemi ,  Ian Poole ,  Costas Plakas ,  Jim Piper

IPC: G06K9/34

CPC classification number: G06T7/11 ,  G06T2207/20128 ,  G06T2207/30004 ,  Y10S128/922 ,  Y10S128/923 ,  Y10S128/924

Abstract: According to one embodiment there is provided a method of selecting a plurality of M atlases from among a larger group of N candidate atlases to form a multi-atlas data set to be used for computer automated segmentation of novel image data sets to mark objects of interest therein. A set of candidate atlases is used containing a reference image data set and segmentation data. Each of the candidate atlases is segmented against the others in a leave-one-out strategy, in which the candidate atlases are used as training data for each other. For each candidate atlas in turn, the following is carried out: registering; segmenting; computing an overlap; computing a value of the similarity measure for each of the registrations; and obtaining a set of regression parameters by performing a regression with the similarity measure being the independent variable and the overlap being the dependent variable. The M atlases are then selected from among all the N candidate atlases to form the multi-atlas data set, the M atlases being those atlases determined to collectively provide the highest aggregate overlap over all the training data image sets.

Abstract translation: 根据一个实施例，提供了一种从较大组的N个候选地图集中选择多个M个遗传数据的方法，以形成用于新颖图像数据集的计算机自动分割以标记感兴趣的对象的多图谱数据集 其中。 使用一组候选地图集，其中包含参考图像数据集和分割数据。 候选地图集中的每一个都按照一个一个出发的策略与其他地图集分割，其中候选地图集被用作彼此的训练数据。 依次对每个候选图集进行以下操作：注册; 分段; 计算重叠; 计算每个注册的相似性度量的值; 以及通过使用所述相似性度量作为所述独立变量进行回归并且所述重叠是因变量来获得一组回归参数。 然后，从所有N个候选地图集中选出M个图集以形成多图集数据集，M个图集被确定为在所有训练数据图像集上统一提供最高的聚集重叠。

公开(公告)号：US20110211745A1

公开(公告)日：2011-09-01

申请号：US13105764

申请日：2011-05-11

Applicant: Shashidhar Sathyanarayana

Inventor： Shashidhar Sathyanarayana

IPC: G06K9/00

CPC classification number: G06K9/6292 ,  G06T7/11 ,  G06T2207/10132 ,  G06T2207/30101 ,  Y10S128/92 ,  Y10S128/921 ,  Y10S128/922 ,  Y10S128/923 ,  Y10S128/924

Abstract: The systems and methods described herein provide for fast and accurate image segmentation through the application of a multi-stage classifier to an image data set. An image processing system is provided having a processor configured to apply a multi-stage classifier to the image data set to identify a distinctive region. The multi-stage classifier can include two or more component classifiers. The first component classifier can have a sensitivity level configured to identify one or more target regions in the image data set and the second component classifier can have a specificity level configured to confirm the presence of the distinctive region in any identified target regions. Also provided is a classification array having multiple multi-stage classifiers for identification and confirmation of more than one distinctive region or for the application of different classification configurations to the image data set to identify a specific distinctive region.

Abstract translation: 本文描述的系统和方法通过将多级分类器应用于图像数据集来提供快速和准确的图像分割。 提供一种图像处理系统，其具有被配置为将多级分类器应用于图像数据集以识别特征区域的处理器。 多级分类器可以包括两个或多个分量分类器。 第一分量分类器可以具有被配置为识别图像数据集中的一个或多个目标区域的灵敏度级别，并且第二分量分类器可以具有被配置为确认任何识别的目标区域中特征区域的存在的特异性级别。 还提供了一种具有多个多级分类器的分类阵列，用于识别和确认多于一个的特征区域，或者为了识别特定区域而将图像数据集应用于不同的分类配置。

公开(公告)号：US20110190599A1

公开(公告)日：2011-08-04

申请号：US13019882

申请日：2011-02-02

Applicant: Hui Wang ,  Scott Amundson ,  Robin Boyce ,  James Ochs ,  Li Li ,  Steve Vargas ,  Tonia Madere

Inventor： Hui Wang ,  Scott Amundson ,  Robin Boyce ,  James Ochs ,  Li Li ,  Steve Vargas ,  Tonia Madere

IPC: A61B5/00

CPC classification number: G06F19/34 ,  A61B5/04 ,  A61B5/04004 ,  A61B5/0402 ,  A61B5/0476 ,  A61B5/0484 ,  A61B5/0496 ,  A61B5/0806 ,  A61B5/14542 ,  A61B5/14551 ,  A61B5/4818 ,  A61B2505/01 ,  A61B2505/03 ,  G06F19/00 ,  G06K9/00496 ,  G06K9/6256 ,  G06K9/6292 ,  G06K9/6293 ,  G16H15/00 ,  G16H50/20 ,  G16H50/70 ,  Y10S128/92 ,  Y10S128/923 ,  Y10S128/924 ,  Y10S128/925 ,  Y10S706/924

Abstract: Various embodiments may provide methods and systems capable of evaluating physiological parameter data. The methods and systems may include a receiver capable of collecting a signal representative of a physiological status of a patient, a plurality of data analysis components, wherein each of the plurality of data analysis components is capable of generating a metric based on the signal, and an arbitrator communicatively coupled to each of the plurality of data analysis components and capable of generating a single metric from the metrics generated by the plurality of data analysis components.

Abstract translation: 各种实施例可以提供能够评估生理参数数据的方法和系统。 所述方法和系统可以包括能够收集表示患者的生理状况的信号的接收机，多个数据分析部件，其中所述多个数据分析组件中的每一个能够基于所述信号生成度量，以及 通信地耦合到所述多个数据分析组件中的每一个并且能够根据由所述多个数据分析组件生成的度量来生成单个度量的仲裁器。

公开(公告)号：US07979378B2

公开(公告)日：2011-07-12

申请号：US12566212

申请日：2009-09-24

Applicant: Jeff West ,  Jay A. Tzucker ,  Mahesh Maddali ,  James Kalgren

Inventor： Jeff West ,  Jay A. Tzucker ,  Mahesh Maddali ,  James Kalgren

IPC: G06N5/02 ,  A61B5/00 ,  A61N1/00

CPC classification number: G16H40/63 ,  G06F19/00 ,  Y10S128/924 ,  Y10S439/909 ,  Y10S706/924

Abstract: This document discusses, among other things, a user interface capable of resolving interactions between programmable parameters for operation of a personal medical device. Programming these devices is a difficult task when many parameters are involved. The medical device interface attempts to reduce and minimize constraint violations between interdependent parameters using an initial set of parameter values supplied by user (typically a physician) input, and constraint violations describing invalid parameter values. A user is given the option to select one or more parameters to remain constant. If possible, a set of parameter values with less egregious constraint violations is displayed to the user. A user is prompted to accept the set of parameter values and program the medical device.

Abstract translation: 本文件还讨论了能够解决用于个人医疗设备的操作的可编程参数之间的交互的用户界面。 当涉及许多参数时，对这些设备进行编程是一项艰巨的任务。 医疗设备接口尝试使用由用户（通常是医师）输入提供的初始参数值集合以及描述无效参数值的约束违例来减少并最小化相互依赖参数之间的约束违规。 用户可以选择一个或多个参数保持不变。 如果可能，向用户显示一组不太严重的约束违规的参数值。 提示用户接受一组参数值并对医疗设备进行编程。

公开(公告)号：US07613672B2

公开(公告)日：2009-11-03

申请号：US11380570

申请日：2006-04-27

Applicant: Jeff West ,  Jay A. Tzucker ,  Mahesh Maddali ,  James Kalgren

Inventor： Jeff West ,  Jay A. Tzucker ,  Mahesh Maddali ,  James Kalgren

IPC: G06N5/02 ,  A61B5/00 ,  A61N1/00

CPC classification number: G16H40/63 ,  G06F19/00 ,  Y10S128/924 ,  Y10S439/909 ,  Y10S706/924

Abstract: This document discusses, among other things, a user interface capable of resolving interactions between programmable parameters for operation of a personal medical device. Programming these devices is a difficult task when many parameters are involved. The medical device interface attempts to reduce and minimize constraint violations between interdependent parameters using an initial set of parameter values supplied by user (typically a physician) input, and constraint violations describing invalid parameter values. A user is given the option to select one or more parameters to remain constant. If possible, a set of parameter values with less egregious constraint violations is displayed to the user. A user is prompted to accept the set of parameter values and program the medical device.

Abstract translation: 本文件还讨论了能够解决用于个人医疗设备的操作的可编程参数之间的交互的用户界面。 当涉及许多参数时，对这些设备进行编程是一项艰巨的任务。 医疗设备接口尝试使用由用户（通常是医师）输入提供的初始参数值集合以及描述无效参数值的约束违例来减少并最小化相互依赖参数之间的约束违规。 用户可以选择一个或多个参数保持不变。 如果可能，向用户显示一组不太严重的约束违规的参数值。 提示用户接受一组参数值并对医疗设备进行编程。

公开(公告)号：US20090143691A1

公开(公告)日：2009-06-04

申请号：US12165560

申请日：2008-06-30

Applicant: BUDIMIR DRAKULIC

Inventor： BUDIMIR DRAKULIC

IPC: A61B5/0452

CPC classification number: A61B5/0245 ,  A61B5/0002 ,  A61B5/6805 ,  G06Q50/22 ,  G06Q50/24 ,  Y10S128/92 ,  Y10S128/923 ,  Y10S128/924

Abstract: Heart monitor signals indicating a patient's heart characteristics are amplified without affecting the signal characteristics. The amplified heart monitor signals with atypical characteristics are transmitted to a pattern recognition platform which stores the patient's previously provided signals with atypical characteristics. The patient's present and the previously provided signals with atypical characteristics are compared to select the previously provided signals with characteristics closest to those of the presently provided signals. Database signals identifying different types of heart problems in third parties and having characteristics closest to the patient's selected atypical signals are chosen. Dependent upon the severity of the patient's heart problems identified by the chosen database signals, the monitor transmits the chosen database signals to an individual one of the patient's doctor, the patient's hospital and an emergency facility.

Abstract translation: 指示患者心脏特征的心脏监测信号被放大而不影响信号特征。 将具有非典型特征的放大心脏监视器信号传送到模式识别平台，该平台存储患者以前提供的具有非典型特征的信号。 将具有非典型特征的患者存在和先前提供的信号进行比较，以选择具有最接近当前提供的信号特征的先前提供的信号。 选择识别第三方中不同类型的心脏问题并具有最接近患者选择的非典型信号的特征的数据库信号。 根据所选择的数据库信号识别的患者心脏问题的严重程度，监视器将所选择的数据库信号发送给患者医生，患者医院和紧急设施中的一个。

公开(公告)号：US07493264B1

公开(公告)日：2009-02-17

申请号：US10166298

申请日：2002-06-11

Applicant: Miriam A. Kelly ,  Alan M. Lotvin

Inventor： Miriam A. Kelly ,  Alan M. Lotvin

IPC: G06Q50/00

CPC classification number: G06Q50/22 ,  G06F19/00 ,  G06Q10/06 ,  G06Q10/06398 ,  G06Q40/08 ,  G06Q50/24 ,  G16H10/20 ,  G16H50/20 ,  G16H50/30 ,  G16H50/70 ,  Y10S128/903 ,  Y10S128/904 ,  Y10S128/923 ,  Y10S128/924 ,  Y10S128/925

Abstract: An interactive computer assisted method compiles comprehensive health care information on patients in a central repository, assesses and analyzes this information, and identifies high utilizers of health care services using a computer and a user associated therewith. The method includes the steps of creating a central repository of various databases containing patient information, including demographic information and behavior, and optionally the results of a core survey of health status questions. The invention optionally involves the step of determining the appropriate core questions and the criteria to determine whether and when to ask certain questions of particular patients based on their response to prior questions. The invention accurately predicts risk of a medical condition or progression of a medical condition utilizing an interactive administration of a set of core survey questions combined with diagnostic data and places patients efficiently, reliably, and accurately into the appropriate treatment intervention programs. The invention eliminates redundant, repetitive surveying of patients with multiple medical conditions.

Abstract translation: 交互式计算机辅助方法编制中央信息库中患者的综合保健信息，评估和分析此信息，并使用计算机和与之相关的用户识别医疗保健服务的高利用者。 该方法包括创建包含患者信息的各种数据库的中央存储库的步骤，包括人口统计信息和行为，以及可选地对健康状况问题的核心调查结果。 本发明任选地涉及确定适当的核心问题和标准以确定是否以及何时根据其对先前问题的反应来询问特定患者的某些问题的步骤。 本发明利用与诊断数据相结合的一组核心测量问题的交互式管理，准确地预测医疗状况或医疗状况的进展，并将患者有效，可靠和准确地放入适当的治疗干预程序中。 本发明消除了多重医疗状况患者的冗余重复测量。

公开(公告)号：US07458936B2

公开(公告)日：2008-12-02

申请号：US10703024

申请日：2003-11-06

Applicant: Xiang Sean Zhou ,  Dorin Comaniciu ,  Alok Gupta ,  Visvanathan Ramesh ,  Bhavani Duggirala ,  Diane Paine

Inventor： Xiang Sean Zhou ,  Dorin Comaniciu ,  Alok Gupta ,  Visvanathan Ramesh ,  Bhavani Duggirala ,  Diane Paine

IPC: A61B8/00

CPC classification number: G06K9/6276 ,  A61B8/0883 ,  G06F19/00 ,  G06K9/6256 ,  G06K2209/05 ,  G06Q50/22 ,  G16H50/20 ,  Y10S128/92 ,  Y10S128/924

Abstract: A system and method for providing decision support to a physician during a medical examination is disclosed. Data is received from a sensor representing a particular medical measurement. The received data includes image data. The received data and context data is analyzed with respect to one or more sets of training models. Probability values for the particular medical measurement and other measurements to be taken are derived based on the analysis and based on identified classes. The received image data is compared with training images. Distance values are determined between the received image data and the training images, and the training images are associated with the identified classes. Absolute value feature sensitivity scores are derived for the particular medical measurement and other measurements to be taken based on the analysis. The probability values, distance values and absolute value feature sensitivity scores are outputted to the user.

Abstract translation: 公开了一种用于在医学检查期间向医师提供决策支持的系统和方法。 从代表特定医疗测量的传感器接收数据。 所接收的数据包括图像数据。 相对于一组或多组训练模型分析接收到的数据和上下文数据。 特定医疗测量和其他测量的概率值基于分析并基于识别的类别导出。 将接收到的图像数据与训练图像进行比较。 在接收的图像数据和训练图像之间确定距离值，并且训练图像与所识别的类别相关联。 基于分析，针对特定医疗测量和其他测量得出绝对值特征灵敏度得分。 将概率值，距离值和绝对值特征灵敏度得分输出给用户。