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.