Evidence map›Paper›PMID 42332145›Full record

ArticleScientific reports2026

A method for tissue-mask supported whole-body image registration in the UK Biobank.

Yasemin Utkueri, Elin Lundström, Håkan Ahlström, Johan Öfverstedt, Joel Kullberg

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yasemin UtkueriDepartment of Surgical Sciences, Uppsala University, Dag Hammarskjölds Väg 14b, Uppsala, 752 37, Sweden. yasemin.utkueri@uu.se.ORCID 0009-0000-0664-2918
Elin LundströmDepartment of Surgical Sciences, Uppsala University, Dag Hammarskjölds Väg 14b, Uppsala, 752 37, Sweden.
Håkan AhlströmDepartment of Surgical Sciences, Uppsala University, Dag Hammarskjölds Väg 14b, Uppsala, 752 37, Sweden.
Johan ÖfverstedtDepartment of Surgical Sciences, Uppsala University, Dag Hammarskjölds Väg 14b, Uppsala, 752 37, Sweden.
Joel KullbergDepartment of Surgical Sciences, Uppsala University, Dag Hammarskjölds Väg 14b, Uppsala, 752 37, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The UK Biobank is a large-scale study collecting whole-body MR imaging and non-imaging health data. Robust and accurate inter-subject image registration of these whole-body MR images would enable their body-wide spatial standardization, and region-/voxel-wise correlation analysis of non-imaging data with image-derived parameters (e.g., tissue volume or fat content).We propose a sex-stratified inter-subject whole-body MR image registration approach that uses subcutaneous adipose tissue- and muscle-masks from the state-of-the-art VIBESegmentator method to augment intensity-based graph-cut registration. The proposed method (that we refer to as mask-supported) was evaluated on a subset of 4000 subjects by comparing it to an intensity-only method as well as two previously published registration methods, uniGradICON and MIRTK. The evaluation consisted of a comparison of Jacobian Determinant (JD) folding frequency, Dice scores, and voxel-wise label error frequency calculated from the 71 VIBESegmentator masks. The 40 masks from MRSegmentator and 50 masks from TotalSegmentator were also used for independent Dice score evaluations. Additionally, voxel-wise correlation between age and each of fat content and tissue volume was studied to exemplify the usefulness for medical research.The proposed method showed 7percentage points (pp) / 11pp lower frequency of JD folding for males / females when compared to the intensity-based method. The mask-supported method exhibited a mean Dice score of 0.773 / 0.744 across the cohort when evaluated on all VIBESegmentator masks, excluding the two used in the registration, for males / females, respectively. In comparison to the intensity-only registration, the mean values were 6 pp higher for both sexes, and the label error frequency was decreased in most tissue regions. These differences were 9pp / 8pp against uniGradICON and 12pp / 13pp against MIRTK. The mask-supported method achieved a mean Dice score of 0.736 / 0.676 when evaluated with MRSegmentator and 0.683/ 0.617 when evaluated with TotalSegmentator, showing an increase that ranged between 0.7pp and 12pp from the other three methods. Using the proposed method, the age-correlation maps were less noisy and showed higher anatomical alignment. In conclusion, the image registration method using two tissue masks improves whole-body registration of UK Biobank images.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingUK BiobankWhole Body ImagingAdultAgedAlgorithmsBiological Specimen BanksFemaleHumansMaleMiddle AgedUnited KingdomImage registrationSegmentationWhole body MRI

Identifiers

PMID42332145
PMCPMC13287688

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.