构建了超高分辨率多模态脑图谱，支持从整体到细微结构的精准解析。
Ultra-high resolution multimodal MRI densely labelled holistic structural brain atlas
- 融合多尺度标注协议，实现脑结构从器官到亚结构的密集标注
- 基于75名健康人数据，0.125mm³分辨率下生成350类标签
- 适用于神经疾病早期检测与高精度影像分割方法研发
本文提出一种基于多模态高分辨率MRI的人脑结构整体图谱（holiAtlas），覆盖从器官到亚结构的多个解剖层级。该图谱通过整合不同尺度的局部标注协议，利用人类连接组计划数据库中75名健康受试者的T1、T2和白质抑制（WMn）对比图像构建，图像分辨率达0.125 mm³。采用对称组间非线性配准与平均化方法生成均值图谱。在最细粒度层面，共包含350个标签，源自7种不同的勾画协议，并在多尺度上进行分组，形成跨层次一致且连贯的整体脑结构表征。该多尺度、多模态图谱可推动超高清影像分割技术发展，有助于神经系统疾病早期发现，已向科学界公开共享。
原文摘要 · Abstract (English)
In this paper, we introduce a novel structural holistic Atlas (holiAtlas) of the human brain anatomy based on multimodal and high-resolution MRI that covers several anatomical levels from the organ to the substructure level, using a new densely labelled protocol generated from the fusion of multiple local protocols at different scales. This atlas was constructed by averaging images and segmentations of 75 healthy subjects from the Human Connectome Project database. Specifically, MR images of T1, T2 and WMn (White Matter nulled) contrasts at 0.125 $mm^{3}$ resolution were selected for this project. The images of these 75 subjects were nonlinearly registered and averaged using symmetric group-wise normalisation to construct the atlas. At the finest level, the proposed atlas has 350 different labels derived from 7 distinct delineation protocols. These labels were grouped at multiple scales, offering a coherent and consistent holistic representation of the brain across different levels of detail. This multiscale and multimodal atlas can be used to develop new ultra-high-resolution segmentation methods, potentially improving the early detection of neurological disorders. We make it publicly available to the scientific community.
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