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Detalle de: vol2Brain: A New Online Pipeline for Whole Brain MRI Analysis

Title vol2Brain: A New Online Pipeline for Whole Brain MRI Analysis
Abstract

Automatic and reliable quantitative tools for MR brain image analysis are a very valuable resource for both clinical and research environments. In the past few years, this field has experienced many advances with successful techniques based on label fusion and more recently deep learning. However, few of them have been specifically designed to provide a dense anatomical labeling at the multiscale level and to deal with brain anatomical alterations such as white matter lesions (WML). 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 WML. This new pipeline is an evolution of our previous volBrain pipeline that extends significantly the number of regions that can be analyzed. Our proposed method is based on a fast and multiscale multi-atlas label fusion technology with systematic error correction able to provide accurate volumetric information in a few minutes. We have deployed our new pipeline within our platform volBrain ( www.volbrain.upv.es ), which has been already demonstrated to be an efficient and effective way to share our technology with the users worldwide.

Apa Reference Manjón, J.V., Romero, J.E., Vivo-Hernando, R., Rubio, G., Aparici, F., de la Iglesia-Vaya, M. & Coupé, P. (2022). vol2Brain: A New Online Pipeline for Whole Brain MRI Analysis. Frontiers in Neuroinformatics, 16. 10.3389/fninf.2022.862805
Doi 10.3389/fninf.2022.862805
Publication Date 24 May 2022
Publication Type Article
Researcher Maria de-la-Iglesia-Vaya
Ontology Artificial Intelligence, Image analysis, Deep Learning in Biology, Sequence error correction
Research Groups
Tools

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