volBrain

Description
volBrain platform is an online open MRI brain analysis system. It helps researchers all over the world to obtain automatically volumetric brain information from their MRI data without the need of learning complex software packages or having expensive computational infrastructures in their local sites.

volBrain platform works in a fully automatic manner and is able to provide brain analysis without any human interaction in few minutes. Several pipelines dealing with different brain areas and diseases from both mono-modal and multi-modal MRI data are available.

These pipelines process the input image(s) in 10 to 20 minutes. Then, the user receives an email with links to the produced images, a detailled report and a csv file.


Available pipelines:

- pBrain: automatically analyzes and provides quantitative analyses of Parkinson Related structures (Substantia Nigra (locus niger), Red Nucleus and Subthalamic nucleus).

- HIPS: automatically analyzes and provides quantitative analyses of l hippocampal subfields related to several pathologies (multiple sclerosis, Alzheimer's disease, vascular brain injuries, etc.). This module is particularly efficient for the early detection of Alzheimer's disease and Multiple Sclerosis.

- CERES: automatically analyzes cerebellum in brain MRI. It provides expected volume and thickness for each considered structures according to age and sex of the subject under study. It could help to detect volumetric abnormality and thus potential pathology (Multiple Sclerosis, Alzheimer’s disease, schizophrenia, ...).

- volBrain: automatically analyzes whole brain MRI data. It provides volumes for the main IntraCranial Cavity (ICC) tissues (i.e., CSF, GM and WM), of some macroscopic areas such as brain hemispheres, cerebellum and brainstem, and of subcortical structures.

- AssemblyNet: deep learning based segmentation pipeline that automatically analyzes whole brain MRI data. It automatically extract all the brain structures. The volume of brain structures has the potential to be an important biomarker for several neurological diseases (multiple sclerosis, Alzheimer’s disease, Parkinson, etc).

- vol2Brain: automatically analyzes whole brain MRI data. It provides the volumes of the whole brain structures (135 different structures) and the thickness of cortical structures.

- lesionBrain: automatically segments the hyperintensity white matter lesions using a T1w MRI and a FLAIR MRI. DeepLesionBrain classified lesions into several categories according to their position. The volume and the category of the brain lesions have the potential to be important biomarker for several neurological diseases (Multiple Sclerosis, Alzheimer’s disease, lupus, etc).

- DeepLesionbrain: deep learning based segmentation pipeline that automatically segments the hyperintensity white matter lesions using a T1w MRI and a FLAIR MRI. DeepLesionBrain classified lesions into several categories according to their position. The volume and the category of the brain lesions have the potential to be important biomarker for several neurological diseases (Multiple Sclerosis, Alzheimer’s disease, lupus, etc).

- AssemblyNet-AD: deep learning based segmentation pipeline that automatically detects Alzheimer’s Disease (AD) signature in a T1w MRI. Alzheimer’s Disease decision making is based on 3 different types of features: volume of all the brain structures, grading of all the brain structures and atrophy of key structures (hippocampus, amygdala and inferior lateral ventricles). It is able to automatically detect subjects having AD or close to convert to AD within 3y.
Use cases
Clinical trials, Companion diagnostics, Clinical routine, Quantitative Analysis, Computer-Aided Diagnosis, Neurodegenerative diseases, Dementia, Multiple Sclerosis, Alzheimer’s disease, Parkinson, Schizophrenia, Neuroanatomy, Neuroimaging, Medical imaging, MRI segmentation
LaBRI contributors
Pierrick Coupé, Boris Mansencal, Michael Clément, Floréal Morandat
Source code depot
https://github.com/volBrain/
Supported OS
Linux, MacOS, Windows
Latest version
(23/06/2022)
More informations
https://volbrain.net

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