Analysis of brain white matter hyperintensities using pattern recognition techniques

Mariana Bento; Letícia Rittner; Simone Appenzeller; Aline Lapa; Roberto Lotufo

doi:10.1117/12.2006924

13 March 2013 Analysis of brain white matter hyperintensities using pattern recognition techniques

Mariana Bento, Letícia Rittner, Simone Appenzeller, Aline Lapa, Roberto Lotufo

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693P (2013) https://doi.org/10.1117/12.2006924
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The brain white matter is responsible for the transmission of electrical signals through the central nervous system. Lesions in the brain white matter, called white matter hyperintensity (WMH), can cause a significant functional deficit. WMH are commonly seen in normal aging, but also in a number of neurological and psychiatric disorders. We propose here an automatic method for WHM analysis in order to distinguish regions of interest between normal and non-normal white matter (identification task) and also to distinguish different types of lesions based on their etiology: demyelinating or ischemic (classification task). The method combines texture analysis with the use of classifiers, such as Support Vector Machine (SVM), Nearst Neighboor (1NN), Linear Discriminant Analysis (LDA) and Optimum Path Forest (OPF). Experiments with real brain MRI data showed that the proposed method is suitable to identify and classify the brain lesions.

Citation Download Citation

Mariana Bento, Letícia Rittner, Simone Appenzeller, Aline Lapa, and Roberto Lotufo "Analysis of brain white matter hyperintensities using pattern recognition techniques", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693P (13 March 2013); https://doi.org/10.1117/12.2006924

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KEYWORDS

Brain

Feature selection

Magnetic resonance imaging

Image segmentation

Neuroimaging

Pattern recognition

Tissues

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