Bibliographic Details
| Title: |
Using UK Biobank data to establish population-specific atlases from whole body MRI |
| Authors: |
Sophie Starck, Vasiliki Sideri-Lampretsa, Jessica J. M. Ritter, Veronika A. Zimmer, Rickmer Braren, Tamara T. Mueller, Daniel Rueckert |
| Source: |
Communications Medicine, Vol 4, Iss 1, Pp 1-10 (2024) |
| Publisher Information: |
Nature Portfolio, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Medicine |
| Subject Terms: |
Medicine |
| More Details: |
Abstract Background Reliable reference data in medical imaging is largely unavailable. Developing tools that allow for the comparison of individual patient data to reference data has a high potential to improve diagnostic imaging. Population atlases are a commonly used tool in medical imaging to facilitate this. Constructing such atlases becomes particularly challenging when working with highly heterogeneous datasets, such as whole-body images, which contain significant anatomical variations. Method In this work, we propose a pipeline for generating a standardised whole-body atlas for a highly heterogeneous population by partitioning the population into anatomically meaningful subgroups. Using magnetic resonance images from the UK Biobank dataset, we create six whole-body atlases representing a healthy population average. We furthermore unbias them, and this way obtain a realistic representation of the population. In addition to the anatomical atlases, we generate probabilistic atlases that capture the distributions of abdominal fat (visceral and subcutaneous) and five abdominal organs across the population (liver, spleen, pancreas, left and right kidneys). Results Our pipeline effectively generates high-quality, realistic whole-body atlases with clinical applicability. The probabilistic atlases show differences in fat distribution between subjects with medical conditions such as diabetes and cardiovascular diseases and healthy subjects in the atlas space. Conclusions With this work, we make the constructed anatomical and label atlases publically available, with the expectation that they will support medical research involving whole-body MR images. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2730-664X |
| Relation: |
https://doaj.org/toc/2730-664X |
| DOI: |
10.1038/s43856-024-00670-0 |
| Access URL: |
https://doaj.org/article/680bf52f740e463bb2b9f6614a5fe195 |
| Accession Number: |
edsdoj.680bf52f740e463bb2b9f6614a5fe195 |
| Database: |
Directory of Open Access Journals |
