Invention Grant
- Patent Title: Anomaly detection for medical samples under multiple settings
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Application No.: US15447315Application Date: 2017-03-02
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Publication No.: US10108845B2Publication Date: 2018-10-23
- Inventor: Xiaohua Wu , Yan Nei Law
- Applicant: Hong Kong Applied Science and Technology Research Institute Company Limited
- Applicant Address: HK Hong Kong
- Assignee: Hong Kong Applied Science and Technology Research Institute Company Limited
- Current Assignee: Hong Kong Applied Science and Technology Research Institute Company Limited
- Current Assignee Address: HK Hong Kong
- Agency: Spruson & Ferguson (Hong Kong) Limited
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06K9/46 ; G06T7/00 ; G06K9/32 ; G01N33/483 ; G01N21/64

Abstract:
Using multiple imaging modes in whole slide image screening is potentially useful to reduce false positives. To use multiple imaging modes, a method for locating anomalies on a medical sample from an image thereof uses an anomaly-detection process that comprises using plural base classifiers individually to classify an object-of-interest suspected to be an anomaly. Each base classifier respectively extracts features of the object-of-interest and generates, according to the extracted features, a score indicating a likelihood of the object-of-interest being anomalous. The anomaly-detection process further comprises using an aggregate classifier to combine the scores generated by the base classifiers to determine whether the object-of-interest is the anomaly. The aggregate classifier determines a dependability measure for each base classifier according to setting-based variables of a setting under which the sample and the image are obtained, and then selectively combines the scores of the base classifiers according to the dependability measures.
Public/Granted literature
- US20180253589A1 Anomaly Detection for Medical Samples under Multiple Settings Public/Granted day:2018-09-06
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