Invention Grant
- Patent Title: Medical pattern classification using non-linear and nonnegative sparse representations
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Application No.: US15563970Application Date: 2015-06-04
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Publication No.: US10410093B2Publication Date: 2019-09-10
- Inventor: Hien Nguyen , Shaohua Kevin Zhou
- Applicant: Siemens Healthcare GmbH
- Applicant Address: DE Erlangen
- Assignee: Siemens Healthcare GmbH
- Current Assignee: Siemens Healthcare GmbH
- Current Assignee Address: DE Erlangen
- International Application: PCT/US2015/034097 WO 20150604
- International Announcement: WO2016/195683 WO 20161208
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/46

Abstract:
A method of classifying signals using non-linear sparse representations includes learning a plurality of non-linear dictionaries based on a plurality of training signals, each respective nonlinear dictionary corresponding to one of a plurality of class labels. A non-linear sparse coding process is performed on a test signal for each of the plurality of non-linear dictionaries, thereby associating each of the plurality of non-linear dictionaries with a distinct sparse coding of the test signal. For each respective non-linear dictionary included in the plurality of non-linear dictionaries, a reconstruction error is measured using the test signal and the distinct sparse coding corresponding to the respective non-linear dictionary. A particular nonlinear dictionary corresponding to a smallest value for the reconstruction error among the plurality of non-linear dictionaries is identified and a class label corresponding to the particular non-linear dictionary is assigned to the test signal.
Public/Granted literature
- US20180137393A1 MEDICAL PATTERN CLASSIFICATION USING NON-LINEAR AND NONNEGATIVE SPARSE REPRESENTATIONS Public/Granted day:2018-05-17
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