公开(公告)号：US10937157B2

公开(公告)日：2021-03-02

申请号：US16351896

申请日：2019-03-13

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Rongguo Zhang ,  Mengmeng Sun ,  Shaokang Wang ,  Kuan Chen

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.