Search Results for author: Fernando Aparici

Found 3 papers, 0 papers with code

DeepCERES: A Deep learning method for cerebellar lobule segmentation using ultra-high resolution multimodal MRI

no code implementations22 Jan 2024 Sergio Morell-Ortega, Marina Ruiz-Perez, Marien Gadea, Roberto Vivo-Hernando, Gregorio Rubio, Fernando Aparici, Maria de la Iglesia-Vaya, Gwenaelle Catheline, Pierrick Coupé, José V. Manjón

Finally, a new online pipeline, named DeepCERES, has been developed to make available the proposed method to the scientific community requiring as input only a single T1 MR image at standard resolution.

Segmentation

vol2Brain: A new online Pipeline for whole Brain MRI analysis

no code implementations8 Feb 2022 Jose V. Manjon, Jose E. Romero, Roberto Vivo-Hernando, Gregorio Rubio, Fernando Aparici, Mariam de la Iglesia-Vaya, Pierrick Coupe

In this work, we present a fully automatic pipeline (vol2Brain) for whole brain segmentation and analysis which densely labels (N>100) the brain while being robust to the presence of white matter lesions.

Brain Segmentation

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