Invention Grant
- Patent Title: Automated segmentation using deep learned priors
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Application No.: US15367275Application Date: 2016-12-02
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Publication No.: US10453200B2Publication Date: 2019-10-22
- Inventor: Suvadip Mukherjee , Roshni Bhagalia , Xiaojie Huang
- Applicant: GENERAL ELECTRIC COMPANY
- Applicant Address: US NY Schenectady
- Assignee: GENERAL ELECTRIC COMPANY
- Current Assignee: GENERAL ELECTRIC COMPANY
- Current Assignee Address: US NY Schenectady
- Agency: Fletcher Yoder, P.C.
- Main IPC: G06T7/143
- IPC: G06T7/143 ; G06N3/08 ; G06N3/04 ; G06N7/00 ; G06T7/194 ; G06T5/00 ; G06T7/11 ; G06T7/12 ; G06T7/162 ; G06T7/136

Abstract:
Embodiments described herein provide a hybrid technique which incorporates learned pulmonary nodule features in a model based energy minimization segmentation using graph cuts. Features are extracted from training samples using a convolutional neural network, and the segmentation cost function is augmented via the deep learned energy. The system and method improves segmentation performance and more robust initialization.
Public/Granted literature
- US20180122082A1 AUTOMATED SEGMENTATION USING DEEP LEARNED PRIORS Public/Granted day:2018-05-03
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