Deep Learning for Classification of Bone Lesions on Routine MRI.

ABSTRACT:

Background

Radiologists have difficulty distinguishing benign from malignant bone lesions because these lesions may have similar imaging appearances. The purpose of this study was to develop a deep learning algorithm that can differentiate benign and malignant bone lesions using routine magnetic resonance imaging (MRI) and patient demographics.

Methods

1,060 histologically confirmed bone lesions with T1- and T2-weighted pre-operative MRI were retrospectively identified and included, with lesions from 4 institutions used for model development and internal validation, and data from a fifth institution used for external validation. Image-based models were generated using the EfficientNet-B0 architecture and a logistic regression model was trained using patient age, sex, and les

SUBMITTER: Eweje FR 

PROVIDER: S-EPMC8190437 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature