Deep Learning Body Region Classification of MRI and CT Examinations.

ABSTRACT: This study demonstrates the high performance of deep learning in identification of body regions covering the entire human body from magnetic resonance (MR) and computed tomography (CT) axial images across diverse acquisition protocols and modality manufacturers. Pixel-based analysis of anatomy contained in image sets can provide accurate anatomic labeling. For this purpose, a convolutional neural network (CNN)-based classifier was developed to identify body regions in CT and MRI studies. Seventeen CT (18 MRI) body regions covering the entire human body were defined for the classification task. Three retrospective datasets were built for the AI model training, validation, and testing, with a balanced distribution of studies per body region. The test datasets originated from a different heal

SUBMITTER: Raffy P 

PROVIDER: S-EPMC10407003 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature