title: Projecting MRI brain images for the detection of Alzheimer's Disease.
abstract: Recent advances in the process of diagnosis of neurodegenerative diseases, such as Alzheimer's Disease, rely on the use of molecular imaging that allow the interpretation of different metabolic biomarkers in the brain. However these procedures are considered of invasive nature, as they involve the injection of radioactive markers. On the other hand, Magnetic Resonance Imaging (MRI) is perhaps the most widely used and less invasive medical imaging technique, although its ability to detect Alzheimer's Disease has revealed limited. In this paper, a new method that simplifies the process of analysing 3D MRI brain images using a two dimensional projection is proposed. Our system outperforms other methods that use MRI, achieving up to a 86% of accuracy and significantly reducing the computational load. Additionally, it allows the visual analysis and interpretation of the images, which can be of great help in the diagnosis of this and other types of dementia.
authors.affiliation: Dept. of Signal Theory, Networking and Communications, 18071 University of Granada, Spain.
authors.forename: Francisco Jesús
authors.initials: FJ
authors.lastname: Martínez-Murcia
authors.affiliation: Dept. of Signal Theory, Networking and Communications, 18071 University of Granada, Spain.
authors.forename: Juan Manuel
authors.initials: JM
authors.lastname: Górriz
authors.affiliation: Dept. of Signal Theory, Networking and Communications, 18071 University of Granada, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: Ramírez
authors.affiliation: Dept. of Signal Theory, Networking and Communications, 18071 University of Granada, Spain.
authors.forename: Ignacio
authors.initials: I
authors.lastname: Alvarez Illán
authors.affiliation: Dept. of Signal Theory, Networking and Communications, 18071 University of Granada, Spain.
authors.forename: Diego
authors.initials: D
authors.lastname: Salas-González
authors.affiliation: Cyclotron Research Centre, University of Liège, Liège, Belgium.
authors.forename: Fermín
authors.initials: F
authors.lastname: Segovia
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000000981:diagnostic imaging*; D001921:Brain / Q000000981:diagnostic imaging*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged