Novel coronavirus pneumonia detection and segmentation based on the deep-learning method.

ABSTRACT:

Background

Segmentation of coronavirus disease 2019 (COVID-19) lesions is a difficult task due to high uncertainty in the shape, size and location of the lesions. CT scan image is an important means of diagnosing COVID-19, but it requires doctors to observe a large number of scan images repeatedly to determine the patient's condition. Moreover, the low contrast of CT scan and the presence of tissues such as blood vessels in the background increase the difficulty of diagnosis. To solve this problem, we proposed an improved segmentation model called the residual attention U-shaped network (ResAU-Net).

Methods

A novel method to detect and segment coronavirus pneumonia was established based on the deep-learning algorithm. Firstly, the CT scan image was input, and lung segmentati

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC8263886 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature