A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

ABSTRACT:

Purpose

Fractures in vertebral bodies are among the most common complications of osteoporosis and other bone diseases. However, studies that aim to predict future fractures and assess general spine health must manually delineate vertebral bodies and intervertebral discs in imaging studies for further radiomic analysis. This study aims to develop a deep learning system that can automatically and rapidly segment (delineate) vertebrae and discs in MR, CT, and X-ray imaging studies.

Results

We constructed a neural network to output 2D segmentations for MR, CT, and X-ray imaging studies. We trained the network on 4490 MR, 550 CT, and 1935 X-ray imaging studies (post-data augmentation) spanning a wide variety of patient populations, bone disease statuses, and ages from 2005 to 202

SUBMITTER: Suri A 

PROVIDER: S-EPMC8217255 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature