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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/42808

Title: A Structural Parametrization of the Brain Using Hidden Markov Models Based Paths in Alzheimer's Disease
Authors: Martínez-Murcia, Francisco J.
Górriz Sáez, Juan Manuel
Ramírez Pérez de Inestrosa, Javier
Ortiz, Andrés
Issue Date: Apr-2016
Abstract: The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called Computed Aided Diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on Hidden Markov Models. The path is traced using information of intensity and spatial orientation in each node, adapting to the structural changes of the brain. Each path is itself a useful way to extract features from the MRI image, being the intensity levels at each node the most straightforward. However, a further processing consisting of a modification of the Gray Level Co-occurrence Matrix can be used to characterize the textural changes that occur throughout the path, yielding more meaningful values that could be associated to the structural changes in Alzheimer's Disease, as well as providing a significant feature reduction. This methodology achieves high performance, up to 80.3\% of accuracy using a single path in differential diagnosis involving Alzheimer-affected subjects versus controls belonging to the Alzheimer's Disease Neuroimaging Initiative (ADNI).
Sponsorship: TIC218, MINECO TEC2008-02113 and TEC2012-34306 projects, Consejería de Economía, Innovación, Ciencia y Empleo de la Junta de Andalucía P09-TIC-4530 and P11-TIC-710
Publisher: World Scientific Publishing Company
Series/Report no.: International Journal of Neural Systems;26; 1650024
Keywords: HMM
URI: http://hdl.handle.net/10481/42808
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Francisco J. Martinez-Murcia et al. A Structural Parametrization of the Brain Using Hidden Markov Models Based Paths in Alzheimer's Disease. Int. J. Neur. Syst. 26, 1650024 (2016) [15 pages] DOI: http://dx.doi.org/10.1142/S0129065716500246
Appears in Collections:TIC218 - Artículos

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