- Patent Title: Imaging segmentation using multi-scale machine learning approach
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Application No.: US15593497Application Date: 2017-05-12
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Publication No.: US10402979B2Publication Date: 2019-09-03
- Inventor: Mani Abedini , Rajib Chakravorty , Rahil Garnavi , Munawar Hayat
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Fleit Gibbons Gutman Bongini Bianco PL
- Agent Jon A. Gibbons
- Main IPC: G06T7/10
- IPC: G06T7/10 ; G06T7/13 ; G06K9/46 ; G06K9/52 ; G06K9/62 ; G06T7/00 ; G06K9/68 ; G06T7/143 ; G06T7/90 ; G06T7/11

Abstract:
A robust segmentation technique based on multi-layer classification technique to identify the lesion boundary is described. The inventors have discovered a technique based on training several classifiers such that to classify each pixel as lesion versus normal Each classifier is trained on a specific range of image resolutions. Then, for a new test image, the trained classifiers are applied on the image. Then by fusing the prediction results in pixel level a probability map is generated. In the next step, a thresholding method is applied to convert the probability map to a binary mask, which determines a mole border.
Public/Granted literature
- US20170249746A1 IMAGING SEGMENTATION USING MULTI-SCALE MACHINE LEARNING APPROACH Public/Granted day:2017-08-31
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