Reference : Projecting MRI brain images for the detection of Alzheimer’s Disease
Scientific conferences in universities or research centers : Scientific conference in universities or research centers
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/183524
Projecting MRI brain images for the detection of Alzheimer’s Disease
English
Martínez-Murcia, Francisco Jesús [Universidad de Granada (España) = University of Granada (Spain) - UGR > Dept. of Signal Theory, Networking and Communications > > >]
Górriz, Juan Manuel [Universidad de Granada (España) = University of Granada (Spain) - UGR > Dept. of Signal Theory, Networking and Communications > > >]
Ramírez, Javier [Universidad de Granada (España) = University of Granada (Spain) - UGR > Dept. of Signal Theory, Networking and Communications > > >]
Salas-Gonzalez, Diego [Universidad de Granada (España) = University of Granada (Spain) - UGR > Dept. of Signal Theory, Networking and Communications > > >]
Segovia-Román, Fermín mailto [Université de Liège > > Centre de recherches du cyclotron >]
9-Jul-2014
8
International
KES Innovation in Medicine and Healthcare 2014
09/07/2014
San Sebastian (Spain)
Spain
[en] MRI ; Alzheimer's disease ; Computer Aided Diagnosis ; Projections
[en] 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.
http://hdl.handle.net/2268/183524
10.3233/978-1-61499-474-9-225

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