Invention Grant
- Patent Title: Computed Tomography pulmonary nodule detection method based on deep learning
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Application No.: US16351896Application Date: 2019-03-13
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Publication No.: US10937157B2Publication Date: 2021-03-02
- Inventor: Rongguo Zhang , Mengmeng Sun , Shaokang Wang , Kuan Chen
- Applicant: Infervision Medical Technology Co., Ltd.
- Applicant Address: CN Beijing
- Assignee: Infervision Medical Technology Co., Ltd.
- Current Assignee: Infervision Medical Technology Co., Ltd.
- Current Assignee Address: CN Beijing
- Agency: H.C. Park & Associates, PLC
- Priority: CN201810217568.7 20180316
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06N20/00 ; G06N3/08 ; G06T7/11

Abstract:
A computed tomography (CT) pulmonary nodule detection method based on deep learning is provided. The method comprises the steps of: acquiring 3D pulmonary CT sequence images of a user; processing the acquired 3D pulmonary CT sequence images into 2D image data; inputting 2D image data into a preset deep learning network model for training to obtain a trained pulmonary nodule detection model; inputting a set of 3D pulmonary CT sequence images to be tested into the trained pulmonary nodule detection model to obtain a preliminary pulmonary nodule detection result; applying a pulmonary region segmentation algorithm based on deep learning to the preliminary pulmonary nodule detection result to remove false positive pulmonary nodules, so as to obtain a final pulmonary nodule detection result.
Public/Granted literature
- US20190287242A1 COMPUTED TOMOGRAPHY PULMONARY NODULE DETECTION METHOD BASED ON DEEP LEARNING Public/Granted day:2019-09-19
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