Evaluation Of Default Mode Network In Mild Cognitive Impairment And Alzheimer's Disease Individuals

The increasing availability of brain imaging technologies has led to intense neuro scientific inquiry into the human brain.Studies often investigate brain function related to emotion,cognition,language,memory,and numerous other externally induced stimuli as well as resting-state brain function.Studies also use brain imaging in an attempt to determine the functional or structural basis for psychiatric or neurological disorders and,with respect to brain function,to further examine the responses of these disorders to treatment.Neuroimaging is a highly interdisciplinary field and statistics plays a critical role in establishing rigorous methods to extract information and to quantify evidence for formal inferences.In this thesis study,a comprehensive literature review is performed,and a new medical image processing and analysis framework which enables analysis and evaluate of several features in medical images based on sparse representation classification of fMRI data for Alzheimer's disease individuals and Mild Cognitive Impairment using Independent Component Analysis(ICA)method based on FastICA algorithm towards a best classification results.We investigate the analysis of brain connectivity in Alzheimer's disease and Mild Cognitive Impairment patients with fMRI techniques.The focus is on the statistical analysis proposed by each research groups.The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found.Medical images require sequential application of several image post processing techniques in order to be used for quantification and analysis of intended features.Main objective of this thesis study is to build up an application framework,which enables analysis and quantification of several features in medical images with minimized input-dependency over results.Intended application targets to present a software environment,which enables sequential application of medical image processing routines and provides support for radiologists in diagnosis,treatment planning and treatment verification phases of neurodegenerative diseases and brain tumors,thus,reducing the divergence in results of operations applied on medical images.