Development and validation of a fully automated system using deep learning for opportunistic osteoporosis screening using low-dose computed tomography scans

ABSTRACT:

Background

Bone density measurement is an important examination for the diagnosis and screening of osteoporosis. The aim of this study was to develop a deep learning (DL) system for automatic measurement of bone mineral density (BMD) for osteoporosis screening using low-dose computed tomography (LDCT) images.

Methods

This retrospective study included 500 individuals who underwent LDCT scanning from April 2018 to July 2021. All images were manually annotated by a radiologist for the cancellous bone of target vertebrae and post-processed using quantitative computed tomography (QCT) software to identify osteoporosis. Patients were divided into the training, validation, and testing sets in a ratio of 6:2:2 using a 4-fold cross validation method. A localization model using fas

SUBMITTER: Niu X 

PROVIDER: S-EPMC10423368 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature