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

[EN] 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 o...

Descripción completa

Detalles Bibliográficos
Autores: Manjón Herrera, José Vicente|||0000-0001-6640-927X, Morell-Ortega, Sergio|||0009-0001-7639-2915, Rubio Navarro, Gregorio, Ruiz-Perez, Marina, Mansecal, Boris, Le Bot, Edern, Gadea, Marien, Lanuza, Enrique, Catheline, Gwenaelle, Tourdias, Thomas, Planche, Vicent, Giraud, Rémi, Rivière, Denis, Mangin, Jean-Francois, Labra-Avila, Nicole, Vivo-Hernando, Roberto, Aparici-Robles, Fernando, de la Iglesia-Vaya, María, Coupé, Pierrick
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/233308
Acceso en línea:https://riunet.upv.es/handle/10251/233308
Access Level:acceso abierto
Palabra clave:Atlas
Multimodal
Holistic
Segmentation
Brain volume analysis
MRI
Descripción
Sumario:[EN] 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.

Similares en LA Referencia