Comput Methods Programs Biomed - Functional activity maps based on significance measures and Independent Component Analysis.

Tópicos

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Resumo

The use of functional imaging has been proven very helpful for the process of diagnosis of neurodegenerative diseases, such as Alzheimer's Disease (AD). In many cases, the analysis of these images is performed by manual reorientation and visual interpretation. Therefore, new statistical techniques to perform a more quantitative analysis are needed. In this work, a new statistical approximation to the analysis of functional images, based on significance measures and Independent Component Analysis (ICA) is presented. After the images preprocessing, voxels that allow better separation of the two classes are extracted, using significance measures such as the Mann-Whitney-Wilcoxon U-Test (MWW) and Relative Entropy (RE). After this feature selection step, the voxels vector is modelled by means of ICA, extracting a few independent components which will be used as an input to the classifier. Naive Bayes and Support Vector Machine (SVM) classifiers are used in this work. The proposed system has been applied to two different databases. A 96-subjects Single Photon Emission Computed Tomography (SPECT) database from the "Virgen de las Nieves" Hospital in Granada, Spain, and a 196-subjects Positron Emission Tomography (PET) database from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Values of accuracy up to 96.9% and 91.3% for SPECT and PET databases are achieved by the proposed system, which has yielded many benefits over methods proposed on recent works.

Resumo Limpo

use function imag proven help process diagnosi neurodegen diseas alzheim diseas ad mani case analysi imag perform manual reorient visual interpret therefor new statist techniqu perform quantit analysi need work new statist approxim analysi function imag base signific measur independ compon analysi ica present imag preprocess voxel allow better separ two class extract use signific measur mannwhitneywilcoxon utest mww relat entropi re featur select step voxel vector model mean ica extract independ compon will use input classifi naiv bay support vector machin svm classifi use work propos system appli two differ databas subject singl photon emiss comput tomographi spect databas virgen de las niev hospit granada spain subject positron emiss tomographi pet databas alzheim diseas neuroimag initi adni valu accuraci spect pet databas achiev propos system yield mani benefit method propos recent work

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