Review of Machine Learning Classifier Toolbox of Neuroimaging Data

Abstract

Machine learning and artificial neural network is a growing field in medical imaging or neuroimaging in the present decade. Structural and functional neuroimaging is involved in the investigation of diagnosis of brain tumor and mental illness. To acquire the knowledge from previous experience and perception is called learning. Supervised and unsupervised machine learning algorithm also works on the same principles. It trains neuroimaging techniques like fMRI, EEG, MEG & PET data to extract features from the existing information and then predicts or makes decision that are useful for diagnoses in the medical field. The objective of this study is to give overview of machine learning toolbox that is used for analyzing the neuroimaging data without the deep knowledge of programming languages. These entire machine learning tools helps the experts, researchers for further investigation in the field of neuroimaging data.