Computed Tomography pulmonary nodule detection method based on deep learning
US10937157B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2019 |
| Grant date | Mar 2, 2021 |
| Priority date | — |
| Expiry date | Apr 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30064
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.