title: MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.
abstract: MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role.
authors.affiliation: Biomedical Imaging Group Rotterdam, Depts. of Radiology & Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, the Netherlands; Quantib BV, Rotterdam, The Netherlands. Electronic address: w.niessen@erasmusmc.nl.
authors.forename: Wiro J
authors.initials: WJ
authors.lastname: Niessen
mesh_terms: D000375:Aging / Q000235:genetics / Q000378:metabolism*; D015415:Biomarkers / Q000032:analysis* / Q000378:metabolism; D001921:Brain / Q000378:metabolism*; D003704:Dementia / Q000000981:diagnostic imaging* / Q000235:genetics*; D003937:Diagnosis, Differential; D042241:Early Diagnosis; D006801:Humans; D000069550:Machine Learning; D008279:Magnetic Resonance Imaging; D011379:Prognosis
chemical_list: D015415:Biomarkers
keywords: Ageing brain models; Computer aided diagnosis; Dementia; Imaging genetics; Machine learning; Population imaging; Quantitative imaging biomarker