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 0.77 / 0.75 across the cohort and the 71 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.

翻译：UK Biobank是一项收集全身磁共振成像与非成像健康数据的大规模研究。对这些全身磁共振图像进行稳健且准确的跨被试配准，可实现其全身空间标准化，并支持非成像数据与图像衍生参数（如组织体积或脂肪含量）的区域/体素级相关性分析。我们提出了一种性别分层的跨被试全身磁共振图像配准方法，该方法利用最先进的VIBESegmentator方法生成的皮下脂肪组织和肌肉掩模，增强基于强度的图割配准。通过对4000名受试者子集的评估，将所提方法与纯强度方法以及两种已发表的配准方法（uniGradICON和MIRTK）进行比较。评估包括应用于71个VIBESegmentator掩模的重叠度量：1) Dice分数，2) 体素级标签错误频率。此外，通过研究年龄与脂肪含量及组织体积的体素级相关性，以例证其对医学研究的实用性。所提方法在全体队列及71个掩模上，男性/女性的平均Dice分数分别为0.77/0.75。与纯强度配准相比，两性平均Dice分数均高出6个百分点，且大多数组织区域的标签错误频率降低。相较于uniGradICON和MIRTK，该差异分别为9/8个百分点和12/13个百分点。使用所提方法生成的年龄相关性图谱噪声更低，且显示出更高的解剖结构对齐度。综上所述，采用两种组织掩模的图像配准方法改善了UK Biobank图像的全身配准性能。