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<p>In this paper, we introduce a novel structural holistic Atlas (holiAtlas) of human brain anatomy based on multimodal and high-resolution MRI that covers several anatomical levels from the organ level to the substructure level, using a new protocol for dense labelling 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, 3T MR images of T1, T2 and WMn (White Matter nulled) contrasts at 0.125 mm<sup>3</sup> 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.</p>

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Ultra-high resolution multimodal MRI densely labelled holistic structural brain atlas

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月17日

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  • José V. Manjón,
  • Sergio Morell-Ortega,
  • Marina Ruiz-Perez,
  • Boris Mansencal,
  • Edern Le Bot,
  • Marien Gadea,
  • Enrique Lanuza,
  • Gwenaelle Catheline,
  • Thomas Tourdias,
  • Vincent Planche,
  • Remi Giraud,
  • Denis Rivière,
  • Jean-Francois Mangin,
  • Nicole Labra-Avila,
  • Roberto Vivo-Hernando,
  • Gregorio Rubio,
  • Fernando Aparici-Robles,
  • Maria de la Iglesia-Vaya,
  • Pierrick Coupé

摘要

In this paper, we introduce a novel structural holistic Atlas (holiAtlas) of human brain anatomy based on multimodal and high-resolution MRI that covers several anatomical levels from the organ level to the substructure level, using a new protocol for dense labelling 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, 3T MR images of T1, T2 and WMn (White Matter nulled) contrasts at 0.125 mm3 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.