{"ID":2833987,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.02702","arxiv_id":"2512.02702","title":"A method for tissue-mask supported whole-body image registration in the UK Biobank","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 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 comprised overlap measures applied to the 71 VIBESegmentator masks: 1) Dice scores, and 2) voxel-wise label error frequency. 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 exhibited a mean dice score of 0.773 / 0.744 across the cohort and the 69 masks for males/females, respectively. When compared to the intensity-only registration, the mean values were 6 percentage points (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. 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.","short_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...","url_abs":"https://arxiv.org/abs/2512.02702","url_pdf":"https://arxiv.org/pdf/2512.02702v2","authors":"[\"Yasemin Utkueri\",\"Elin Lundström\",\"Håkan Ahlström\",\"Johan Öfverstedt\",\"Joel Kullberg\"]","published":"2025-12-02T12:30:59Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}