Quantitative CT for detecting COVID‑19 pneumonia in suspected cases.

ABSTRACT:

Background

Corona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. The purpose of this study is to explore the diagnostic value of the quantitative computed tomography (CT) method by using different threshold segmentation techniques to distinguish between patients with or without COVID-19 pneumonia.

Methods

A total of 47 patients with suspected COVID-19 were retrospectively analyzed, including nine patients with positive real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR) test (confirmed case group) and 38 patients with negative RT-PCR test (excluded case group). An improved 3D convolutional neural network (VB-Net) was used to automatically extract lung lesions.

SUBMITTER: Lu W 

PROVIDER: S-EPMC8374412 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature