Neuroimaging in Machine Learning for Brain Disorders - Inria - Institut national de recherche en sciences et technologies du numérique
Book Sections Year : 2022

Neuroimaging in Machine Learning for Brain Disorders

Abstract

Medical imaging plays an important role in the detection, diagnosis and treatment monitoring of brain disorders. Neuroimaging includes different modalities such as magnetic resonance imaging (MRI), X-ray computed tomography (CT), positron emission tomography (PET) or single-photon emission computed tomography (SPECT). For each of these modalities, we will explain the basic principles of the technology, describe the type of information the images can provide, list the key processing steps necessary to extract features and provide examples of their use in machine learning studies for brain disorders.
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Dates and versions

hal-03814787 , version 1 (14-10-2022)

Identifiers

  • HAL Id : hal-03814787 , version 1

Cite

Ninon Burgos. Neuroimaging in Machine Learning for Brain Disorders. Olivier Colliot. Machine Learning for Brain Disorders, Springer, In press. ⟨hal-03814787⟩
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