Laparoscopic image smoke removal method based on generative adversarial network
US11935213B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 14, 2023 |
| Grant date | Mar 19, 2024 |
| Priority date | — |
| Expiry date | Mar 14, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A laparoscopic image smoke removal method based on a generative adversarial network, and belongs to the technical field of computer vision. The method includes: processing a laparoscopic image sample to be processed using a smoke mask segmentation network to acquire a smoke mask image; inputting the laparoscopic image sample to be processed and the smoke mask image into a smoke removal network, and extracting features of the laparoscopic image sample to be processed using a multi-level smoke feature extractor to acquire a light smoke feature vector and a heavy smoke feature vector; and acquiring, according to the light smoke feature vector, the heavy smoke feature vector and the smoke mask image, a smoke-free laparoscopic image by filtering out smoke information and maintaining a laparoscopic image by using a mask shielding effect. The method has the technical effects of robustness and ability of being embedded into a laparoscopic device for use.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.