Large-scale UK Biobank Whole Body Atlases

Population atlases are commonly utilised in medical imaging to facilitate the investigation of variability across populations. Such atlases enable the mapping of medical images into a common coordinate system, promoting comparability and enabling the study of inter-subject differences. Constructing such atlases becomes particularly challenging when working with highly heterogeneous datasets, such as whole-body images, where subjects show significant anatomical variations.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 (MR) 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).We demonstrate a clinical application of these atlases, using the differences between subjects with medical conditions such as diabetes and cardiovascular diseases and healthy subjects from the atlas space.With this work, we make the constructed anatomical and label atlases publically available and anticipate them to support medical research conducted on whole-body MR images.人群图谱（population atlases）在医学影像领域常被用于助力跨人群差异的研究。此类图谱可将医学影像映射至统一坐标系，提升影像间的可比性，并支持个体间差异的分析。但在处理高度异质性的数据集（如全身影像）时，由于个体间解剖结构差异显著，构建此类图谱的难度会大幅提升。 本研究提出了一条针对高度异质性人群的标准化全身图谱构建流程：通过将人群划分为具有解剖学意义的亚组，实现标准化全身图谱的生成。本研究依托英国生物样本库（UK Biobank）的磁共振成像（magnetic resonance, MR）数据，构建了六套反映健康人群平均特征的全身图谱。此外，本研究对图谱进行去偏处理，以此得到更贴合真实人群特征的图谱表示。 除解剖学图谱外，本研究还生成了概率图谱，用于刻画人群中腹部脂肪（内脏脂肪与皮下脂肪）及五种腹部器官（肝脏、脾脏、胰腺、左肾与右肾）的分布情况。本研究展示了此类图谱的临床应用场景：通过对比糖尿病、心血管疾病等病患与健康受试者在图谱空间中的差异，开展相关临床研究。 本研究将已构建的解剖学图谱与标注图谱公开共享，期望其能为基于全身磁共振影像的医学研究提供有力支撑。