Large-scale biometry with interpretable neural network regression on UK Biobank body MRI.

ABSTRACT: In a large-scale medical examination, the UK Biobank study has successfully imaged more than 32,000 volunteer participants with magnetic resonance imaging (MRI). Each scan is linked to extensive metadata, providing a comprehensive medical survey of imaged anatomy and related health states. Despite its potential for research, this vast amount of data presents a challenge to established methods of evaluation, which often rely on manual input. To date, the range of reference values for cardiovascular and metabolic risk factors is therefore incomplete. In this work, neural networks were trained for image-based regression to infer various biological metrics from the neck-to-knee body MRI automatically. The approach requires no manual intervention or direct access to reference segmentations for

SUBMITTER: Langner T 

PROVIDER: S-EPMC7576214 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature