-
Patent Agency Ranking
公开(公告)号：US10438347B2
公开(公告)日：2019-10-08
申请号：US15254798
申请日：2016-09-01
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Dieter Enzmann , William Hsu , Corey W. Arnold , Alex A. T. Bui
IPC: G06K9/00 , G06T7/00 , G06Q50/24 , G06Q10/10 , G16H15/00 , G16H10/00 , G16H80/00 , G16H40/20 , G06F19/00
Abstract: A system is disclosed using a data-driven approach to objectively measure the diagnostic accuracy and value of diagnostic imaging reports using data captured routinely as part of the electronic health record. The system further utilizes the evaluation of the diagnostic accuracy of individual radiologists (imagers), subspecialty sections, modalities, and entire departments based on a comparison against a “precision diagnosis” rendered by other clinical data sources such as pathology, surgery, laboratory tests, etc.
-
2.发明申请公开(公告)号：US20220138949A1
公开(公告)日：2022-05-05
申请号：US17431353
申请日：2020-02-20
Applicant: The Regents of the University of California
Inventor： Dieter Enzmann , William Hsu , Corey Arnold
Abstract: A method for tissue classification includes receiving at least two images associated with a patient, the at least two images being of an anatomical region or tissue. The method also includes identifying a region of interest in the at least two images, analyzing the region of interest to identify changes in the tissue and generating a probability map of the region of interest based on the changes in the tissue. The probability map indicates a likelihood of formation of cancer in the tissue within a predetermined time period. The method also includes displaying the probability map on a display.
-
公开(公告)号：US10939874B2
公开(公告)日：2021-03-09
申请号：US16104131
申请日：2018-08-16
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Kyung Hyun Sung , William Hsu , Shiwen Shen , Xinran Zhong
IPC: A61B5/00 , A61B5/055 , G06T7/00 , G06K9/42 , G06K9/52 , G06K9/62 , G06K9/66 , A61B5/20 , A61B5/08
Abstract: An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.
-
4.发明申请公开(公告)号：US20190183429A1
公开(公告)日：2019-06-20
申请号：US16104131
申请日：2018-08-16
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Kyung Hyun Sung , William Hsu , Shiwen Shen , Xinran Zhong
CPC classification number: A61B5/7267 , A61B5/055 , A61B5/08 , A61B5/201 , A61B5/4244 , A61B5/4381 , G06K9/42 , G06K9/527 , G06K9/6269 , G06K9/66
Abstract: An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.
-
公开(公告)号：US20170053074A1
公开(公告)日：2017-02-23
申请号：US15254798
申请日：2016-09-01
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Dieter Enzmann , William Hsu , Corey W. Arnold , Alex A.T. Bui
CPC classification number: G06T7/0012 , G06F19/321 , G06Q10/103 , G06Q50/24 , G06T2207/10116 , G06T2207/30068 , G06T2207/30096 , G16H10/00 , G16H15/00 , G16H40/20 , G16H80/00
Abstract: A system is disclosed using a data-driven approach to objectively measure the diagnostic accuracy and value of diagnostic imaging reports using data captured routinely as part of the electronic health record. The system further utilizes the evaluation of the diagnostic accuracy of individual radiologists (imagers), subspecialty sections, modalities, and entire departments based on a comparison against a “precision diagnosis” rendered by other clinical data sources such as pathology, surgery, laboratory tests, etc.
Abstract translation: 公开了使用数据驱动方法来客观地测量诊断成像报告的诊断准确性和价值的系统，该系统常规地作为电子健康记录的一部分捕获。 基于与其他临床数据来源（如病理，手术，实验室检查等）提供的“精确诊断”的比较，该系统进一步利用个体放射科医师（成像器），亚专科，模式和整个部门的诊断准确性的评估， 等等
-
-
-
-
Search Results
5
records
(took 0.02 seconds)
