Invention Grant
- Patent Title: Disease detection algorithms trainable with small number of positive samples
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Application No.: US17221146Application Date: 2021-04-02
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Publication No.: US11922682B2Publication Date: 2024-03-05
- Inventor: Mehdi Moradi , Chun Lok Wong
- Applicant: MERATIVE US L.P.
- Applicant Address: US MI Ann Arbor
- Assignee: MERATIVE US L.P.
- Current Assignee: MERATIVE US L.P.
- Current Assignee Address: US MI Ann Arbor
- Agency: Foley Hoag LLP
- Agent Erik A. Huestis; Lee Chedister
- Main IPC: G06V10/82
- IPC: G06V10/82 ; G06F18/24 ; G06N3/044 ; G06N3/045 ; G06N3/047 ; G06N3/08 ; G06N5/01 ; G06N20/00 ; G06N20/10 ; G06N20/20 ; G06T7/00 ; G06V10/764 ; G06V20/69 ; G16H30/40 ; G16H50/20 ; G16H50/70

Abstract:
Disease detection from medical images is provided. In various embodiments, a medical image of a patient is read. The medical image is provided to a trained anatomy segmentation network. A feature map is received from the trained anatomy segmentation network. The feature map indicates the location of at least one feature within the medical image. The feature map is provided to a trained classification network. The trained classification network was pre-trained on a plurality of feature map outputs of the segmentation network. A disease detection is received from the trained classification network. The disease detection indicating the presence or absence of a predetermined disease.
Public/Granted literature
- US20210224995A1 DISEASE DETECTION ALGORITHMS TRAINABLE WITH SMALL NUMBER OF POSITIVE SAMPLES Public/Granted day:2021-07-22
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