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1. 发明申请

WO2015066650A1 EVOLVING CONTEXTUAL CLINICAL DATA ENGINE FOR MEDICAL INFORMATION 审中-公开
标题翻译：展示医疗信息的临床数据引擎
公开(公告)号：WO2015066650A1
公开(公告)日：2015-05-07
申请号：PCT/US2014/063752
申请日：2014-11-03
申请人： TERARECON, INC. , SORENSON, Jeffrey
发明人： SORENSON, Jeffrey
IPC分类号： G06F19/00
CPC分类号： G06F19/322 , G06F19/00 , G06Q50/24 , G16H10/60 , G16H50/20
摘要： A medical information server receives a signal from a client device over a network, representing a first user interaction of a user with respect to first medical information displayed to a user. A user interaction analyzer invokes a first set of ECCD rules associated with the user based on the first user interaction to determine medical data categories that the user is likely interested in. The first set of ECCD rules was generated by an ECCD engine based on prior user interactions of the user. A data retrieval module accesses medical data servers corresponding to the medical data categories to retrieve medical data of the medical data categories. A view generator integrates the retrieved medical data to generate one or more views of second medical information and transmits the views of second medical information to a client device to be displayed on a display of the client device.
摘要翻译：医疗信息服务器通过网络从客户端设备接收信号，代表用户相对于向用户显示的第一医疗信息的第一用户交互。用户交互分析器基于第一用户交互来调用与用户相关联的第一组ECCD规则，以确定用户可能感兴趣的医疗数据类别。第一组ECCD规则由基于先前用户的ECCD引擎生成用户的互动数据检索模块访问对应于医疗数据类别的医疗数据服务器，以检索医疗数据类别的医疗数据。视图生成器将检索到的医疗数据集成以产生第二医疗信息的一个或多个视图，并将第二医疗信息的视图发送到客户端设备，以显示在客户端设备的显示器上。

2. 发明申请

WO2015175799A1 EVOLVING CONTEXTUAL CLINICAL DATA ENGINE FOR MEDICAL DATA PROCESSING 审中-公开
标题翻译：用于医疗数据处理的演示临床数据引擎
公开(公告)号：WO2015175799A1
公开(公告)日：2015-11-19
申请号：PCT/US2015/030821
申请日：2015-05-14
申请人： TERARECON, INC.
发明人： ZHAO, Tiecheng , SORENSON, Jeffrey , IWASE, Akio
IPC分类号： G06F19/00
CPC分类号： G06F19/321 , G06F19/00 , G16H10/60 , G16H40/63 , G16H50/20 , G16H50/70
摘要： A medical information server receives a signal from a client device representing a first user interaction with first medical data associated with a first medical condition of a patient received from a first medical data server. A data retrieval module accesses a second medical data server to retrieve second medical data of the patient that is related to the first medical data. A data analysis module automatically performs a first analysis on image data of the first medical data to generate image quantitative result and a second analysis on the image quantitative result in view of other medical data of the patient to determine a likelihood of a second medical condition of the patient based on the analysis. A data integrator integrates the second medical data with an analysis result of the analysis to generate and transmit a view of medical information to the client device to be displayed therein.
摘要翻译：医疗信息服务器从客户端设备接收表示与从第一医疗数据服务器接收到的患者的第一医疗状况相关联的第一医疗数据的第一用户交互的信号。数据检索模块访问第二医疗数据服务器以检索与第一医疗数据相关的患者的第二医疗数据。数据分析模块自动执行对第一医疗数据的图像数据的第一次分析以产生图像定量结果，以及根据患者的其他医疗数据的图像定量结果的第二次分析，以确定患者的第二医疗状况的可能性病人根据分析。数据积分器将第二医疗数据与分析的分析结果集成，以生成并发送医疗信息的视图到要在其中显示的客户端设备。

3. 发明申请

WO2018044872A1 SYSTEM AND METHOD FOR MEDICAL IMAGING INFORMATICS PEER REVIEW SYSTEM 审中-公开
标题翻译：用于医学成像信息同级评审系统的系统和方法
公开(公告)号：WO2018044872A1
公开(公告)日：2018-03-08
申请号：PCT/US2017/049095
申请日：2017-08-29
申请人： TERARECON, INC. , SORENSON, Jeffrey , ZHAO, Tiecheng , MACCUTCHEON, David W. , TAYLOR, Jacob Ian , HERSCU, Misha , KUHN, Gael , ROTHENBERG, Steven
发明人： SORENSON, Jeffrey , ZHAO, Tiecheng , MACCUTCHEON, David W. , TAYLOR, Jacob Ian , HERSCU, Misha , KUHN, Gael , ROTHENBERG, Steven
IPC分类号： G06F19/00
摘要： Image processing engines can be utilized to inject studies into other commercial or independently-developed peer review systems which are designed to review the medical findings identified by a set of physicians. Image processing engines detect, confirm or verify findings by physicians or other engines, where the engines operate as peer reviewers. The engines can prospectively "learn" from the feedback when these images are reviewed by the physicians during diagnostic interpretation creating a closed-loop quality assurance process and fostering a community platform approach to engine development which is supported by the security, governance, access control, regulatory compliance and other features of the Peer Review System. Utilizing machine learning based on the data collected from peer review, the Peer Review System can adapt and improve its performance as well as the measured performance of the physicians using the system for diagnostic interpretation.
摘要翻译：图像处理引擎可用于将研究注入其他商业或独立开发的同行评审系统，该系统旨在审查由一组医生确定的医学发现。图像处理引擎检测，确认或核实医生或其他引擎的结果，引擎在引擎中作为同行评审者进行操作。引擎可以前瞻性地“学习” 从反馈时，医师在诊断解释过程中对这些图像进行审查，创建一个闭环质量保证流程，并促进社区平台的发动机开发方法，并由安全，治理，访问控制，法规遵从和其他功能支持的引擎开发。同行评审制度。利用基于从同行评审收集的数据的机器学习，同行评审系统可以调整和改进其性能以及使用该系统进行诊断解读的医生的测量表现。

4. 发明申请

WO2018093921A1 SYSTEM AND METHOD FOR THREE-DIMENSIONAL PRINTING, HOLOGRAPHIC AND VIRTUAL REALITY RENDERING FROM MEDICAL IMAGE PROCESSING 审中-公开
公开(公告)号：WO2018093921A1
公开(公告)日：2018-05-24
申请号：PCT/US2017/061833
申请日：2017-11-15
申请人： TERARECON, INC.
发明人： KUHN, Gael , ZHAO, Tiecheng , GUIGONIS, David , SORENSON, Jeffrey , MACCUTCHEON, David
IPC分类号： G06K9/00 , G06T7/30
摘要： A work flow is provided through a network. A network server receives through the network a request to convert 3D segmented medical image data to information print-ready for printing on a 3D printer or rendered for viewing. Access to converted data is limited to one or more authorized users. The 3D segmented medical image data to a converted data file. The converted data file is in a medical image data file format that allows multiple sub-segmentation of a particular human anatomy or region of interest. The medical image data file format allows for storage of mask segmentation information, color palette, shadowing, transparency and opacity.

5. 发明申请

WO2018093865A1 MEDICAL IMAGE IDENTIFICATION AND INTERPRETATION 审中-公开
公开(公告)号：WO2018093865A1
公开(公告)日：2018-05-24
申请号：PCT/US2017/061756
申请日：2017-11-15
申请人： TERARECON, INC.
发明人： SORENSON, Jeffrey , MACCUTCHEON, David , ZHAO, Tiecheng , KUHN, Gael
IPC分类号： G06F17/30 , G06K9/78
摘要： An artificial intelligence findings system includes an artificial intelligence findings system. An image identification engine receives new image data pertaining to a patient and past reports and image data pertaining to the patient. The image identification engine uses the past image data pertaining to the patient to identify for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A findings engine receives new image data and processes the new image data to generate findings based on the new image data and based on the identified for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A communication interface provides the findings to a diagnostic review system that presents the findings to a user. An adjustment engine receives notifications of changes to findings made by a user when using the medical image interpretation system.

6. 发明申请

WO2018071575A1 SYSTEM AND METHOD FOR MEDICAL IMAGE INTERPRETATION 审中-公开
标题翻译：用于医学图像解释的系统和方法
公开(公告)号：WO2018071575A1
公开(公告)日：2018-04-19
申请号：PCT/US2017/056191
申请日：2017-10-11
申请人： TERARECON, INC.
发明人： SORENSON, Jeffrey , MACCUTCHEON, David , ZHAO, Tiecheng , KUHN, Gael , HERSCU, Misha , TAYLOR, Jacob , ROTHENBERG, Steven
IPC分类号： G06K9/00
摘要： An artificial intelligence findings system includes a findings engine that receives medical image data and generates findings based on the medical image data and image interpretation algorithms that take into account stored preferences for a user. A client viewer presents the findings to the user. An adjustment engine allows the user to adjust the findings to produce a report. A tracking module tracks findings and adjustments made to the findings by the user when producing the report. The tracking module produces tracking information. A machine learning engine receives the tracking information and based on the adjustments made to the findings by the user adjusts the stored preferences for the user.
摘要翻译：人工智能发现系统包括接收医学图像数据并且基于医学图像数据和图像解读算法生成发现的发现引擎，所述算法考虑了存储的用户偏好。客户浏览器向用户呈现发现。调整引擎允许用户调整结果以产生报告。跟踪模块跟踪用户在制作报告时对结果所做的调查结果和调整。跟踪模块产生跟踪信息。机器学习引擎接收跟踪信息并且基于用户对发现进行的调整来调整为用户存储的偏好。

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