Does non-COVID-19 lung lesion help? investigating transferability in COVID-19 CT image segmentation.

ABSTRACT:

Background and objective

Coronavirus disease 2019 (COVID-19) is a highly contagious virus spreading all around the world. Deep learning has been adopted as an effective technique to aid COVID-19 detection and segmentation from computed tomography (CT) images. The major challenge lies in the inadequate public COVID-19 datasets. Recently, transfer learning has become a widely used technique that leverages the knowledge gained while solving one problem and applying it to a different but related problem. However, it remains unclear whether various non-COVID19 lung lesions could contribute to segmenting COVID-19 infection areas and how to better conduct this transfer procedure. This paper provides a way to understand the transferability of non-COVID19 lung lesions and a better strategy

SUBMITTER: Wang Y 

PROVIDER: S-EPMC7899930 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature