A Review of Feature Reduction Techniques in Neuroimaging

• Published in: Neuroinformatics (Totowa, N.J.) Vol. 12; no. 2; pp. 229 - 244
• Main Authors: Mwangi, Benson, Tian, Tian Siva, Soares, Jair C.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.04.2014; Springer; Springer Nature B.V
• Subjects: Applied sciences; Artificial Intelligence; Bioinformatics; Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; Brain - physiology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Computer science; control theory; systems; Data processing. List processing. Character string processing; Exact sciences and technology; Humans; Investigative techniques, diagnostic techniques (general aspects); Learning and adaptive systems; Medical sciences; Memory organisation. Data processing; Nervous system; Neuroimaging - methods; Neuroimaging - statistics & numerical data; Neurology; Neurosciences; Pattern recognition. Digital image processing. Computational geometry; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Review; Software; Statistics as Topic; Dimensionality reduction; Predictive Modeling; Neuroimaging; Feature selection; Machine learning; Multivariate; Feature reduction; Central nervous system; Modeling; Encephalon; Multidimensional analysis; Voxel; Selection criterion; Age; Medical application; Computer vision; Data analysis; Redundancy; Inference; Data reduction; Dimension reduction; Discrimination; Medical imagery; Tridimensional image; Artificial intelligence

Machine learning techniques are increasingly being used in making relevant predictions and inferences on individual subjects neuroimaging scan data. Previous studies have mostly focused on categorical discrimination of patients and matched healthy controls and more recently, on prediction of individ...