ArticleCommunications medicine2024
Using UK Biobank data to establish population-specific atlases from whole body MRI.
Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A method for tissue-mask supported whole-body image registration in the UK Biobank.Scientific reports · 2026Article
- Local and global patterns support medical imaging as a biomarker of ageing.Communications medicine · 2026Article
- VIBESegmentator: full body MRI segmentation for the NAKO and UK Biobank.European radiology · 2026Article
- Neck-to-knee dixon MRI thigh volume as a superior mass biomarker for Sarcopenia: evidence from the UK biobank.NPJ digital medicine · 2026Article
- Clinically validated dataset of 435 human colons segmented from CT colonography.Scientific data · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundReliable 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.
methodIn 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).
resultsOur 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.
conclusionsWith 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.
Identifiers
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Registered trials
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