Biomedical Image Processing / Medical Image Processing
Mahdieh Ghasemi
Volume 12, Issue 1 , June 2018, , Pages 51-61
Abstract
Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Different pathological attacks in Parkinson’s disease can be investigated by directional relations in the base spontaneous fluctuations of the brain from the resting ...
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Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Different pathological attacks in Parkinson’s disease can be investigated by directional relations in the base spontaneous fluctuations of the brain from the resting state functional magnetic resonance imaging (RS-fMRI) data. In this paper, for analyzing the directional brain network at rest, Directed Transform Function (DTF) technique with graph theory has been used in two frequency sub-bands and intra/inter group connectivities were compared by statistical analysis. The result of group comparison between PD and healthy which has been done, showed that there are more significant connections in the low frequency band in Parkinson’s disease and control group compared to high frequency band. The relation between basal ganglia and cerebellum has been disturebed in Parkinson’s disease. Furthermore, some brain regions such as left cerebellum has the most information flow in healthy group which characterized by pivotal regions which were influenced by the other brain regions, this connection became disordered in Parkinsonism.
Biomedical Image Processing / Medical Image Processing
Mahdie Ghasemi; Ali Mahloojifar; Mehdi Omidi
Volume 8, Issue 3 , September 2014, , Pages 261-275
Abstract
Functional changes in the brain motor network are responsible for the major clinical features of Parkinson’s disease (PD). Recent studies on investigation of the brain function show that there are spontaneous fluctuations between regions at rest as resting state network affected in various disorders. ...
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Functional changes in the brain motor network are responsible for the major clinical features of Parkinson’s disease (PD). Recent studies on investigation of the brain function show that there are spontaneous fluctuations between regions at rest as resting state network affected in various disorders. In this paper, we examine changes of functional dependency between brain regions of interest associated with known anatomical pathology in Parkinson Disease (PD) using copula theory on resting state fMRI. Five types of copulas were tested: Gaussian and t (Euclidean), Clayton, Gumbel and Frank (Archimedean). We used an efficient maximum likelihood procedure for estimating copula parameters. Goodness of fits was tested using root mean square error (RMSE) and kulback-leibler divergence between each copula function and joint empirical cumulative distribution. Control vs PD group comparison was also done on dependency parameter using parametric and nonparametric tests. The results show that functional dependency between cerebellum and basal ganglia is much stronger in PD than in control. In this paper, we proposed for the first time that joint distribution characteristics could potentially provide information on discriminative features for functional connectivity analysis between healthy and patients.
