Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Hessam Ahmadi; Emad Fatemizadeh; Alimotie Nasrabadi
Volume 14, Issue 3 , October 2020, , Pages 235-249
Abstract
Functional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging technique for analyzing the brain functions through low-frequency fluctuations called the Blood-Oxygen-Level-Dependent (BOLD) signals. Measurement of the functional connectivity in brain networks is usually done by the fMRI time-series ...
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Functional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging technique for analyzing the brain functions through low-frequency fluctuations called the Blood-Oxygen-Level-Dependent (BOLD) signals. Measurement of the functional connectivity in brain networks is usually done by the fMRI time-series through Pearson Correlation Coefficients (PCC). As the PCC shows linear dependencies, in this study, non-linear relationships in the fMRI signals of the patients with Alzheimer's Disease (AD) were investigated using the kernel trick method. Kernel trick approach maps the input information into a higher dimension space and implements the linear calculations in a new space that is proportionate to the non-linear relationships in the primary space. After generating the weighted undirected brain graphs based on the Automated Anatomical Labeling (AAL) atlas, different kernel functions with different parameters were applied. Then the graph global measures including degree, strength, small-worldness, modularity, and efficiencies features were computed and the non-parametric permutation test was performed. According to the results, the kernel trick method showed more significant differences with AD and healthy subjects in comparison with the simple PCC and it could be because of the non-linear correlations that are not captured by the PCC. Among different kernel functions, the Polynomial function had the best performance. Applying this kernel, the classification was done by the Support Vector Machine (SVM) classifier. The achieved accuracy was equal to 98.68±0.79%. The Occipital and Temporal lobes and also the Default Mode Network (DMN) were analyzed and the kernel trick method showed more significant differences in all of them. It is worthwhile to mention that the right and left Angular areas of DMN showed no significant changes in none of the methods and it could be concluded that the AD does not affect this areas effectively.
Biomedical Image Processing / Medical Image Processing
Somayeh Maleki Balajoo; Davoud Asemani; Hamid Soltanian-Zadeh
Volume 12, Issue 2 , September 2018, , Pages 111-124
Abstract
Early alterations of functional connectivity (FC) within the default mode network (DMN) have been reported in Alzheimer’s disease (AD). Recently, the resting-state brain networks have been described with non-stationary profiles since inter- and intra-FC of the brain networks changes over time, ...
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Early alterations of functional connectivity (FC) within the default mode network (DMN) have been reported in Alzheimer’s disease (AD). Recently, the resting-state brain networks have been described with non-stationary profiles since inter- and intra-FC of the brain networks changes over time, even at rest. To fully understand the FC changes that characterize AD, the underlying change of its dynamic pattern needs to be captured. The purpose of this study was to evaluate dynamic FC (dFC) patterns within the DMN in patients with AD relative to healthy aging. Here, a sparse logistic regression (SLR) model was employed to estimate the dFC networks in patients with AD (n = 24) compared with healthy control group (n = 37) using resting-state functional magnetic resonance imaging (rs-fMRI) data. To analyze the dFC network, we introduced a temporal variability-functional pattern (TV-FP) score, which shows how the functional pattern of a given region changes over time. This score is able to quantify the temporal patterns of regions involved in a dFC network. We compared TV-FP score across groups. The results indicate that the main regions of DMN, such as the anterior medial prefrontal cortex (aMPFC) and lateral temporal cortex (LTC), are associated with a significantly increased TV-FP score in the AD group when compared to the HC group. The FC pattern of these regions is impaired in AD according to a conventional static functional connectivity (sFC) analysis. These findings may suggest that aMPFC and LTC may tend to reorganize their functional pattern to compensate for the related functional deficiency due to AD.
Nanobiotechnology / Bionanotechnology / Nanobiology
Mah Monir Karimzade; Ladan Rashidi; Fariba Ganji; Mitra Ahmadi; Sattar Tahmasebi Enferadi
Volume 8, Issue 4 , February 2015, , Pages 385-398
Abstract
The aim of this research is the preparation of a system based on mesoporous silica nanoparticles (MSN) for delivery of Rivastigmine hydrogen tartrate and investigating of the system cytotoxicity, with or without drugs, on the human brain neuroblastoma cells (SY5Y). Rivastigmine is a hydrophilic and a ...
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The aim of this research is the preparation of a system based on mesoporous silica nanoparticles (MSN) for delivery of Rivastigmine hydrogen tartrate and investigating of the system cytotoxicity, with or without drugs, on the human brain neuroblastoma cells (SY5Y). Rivastigmine is a hydrophilic and a hydrophobic drug which is used for treatment of Alzimerʾs disease. In this study MSN were synthesized and characterized by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, x-ray diffraction, N2 adsorption isotherms, and z-potential analysis. Results showed that all MSN were spherical with the same structure. The mean size of nanoparticles was 100±13 nm and the mean diameter of pores was 2.15 nm. The loading capacity and efficiency of rivastigmine hydrogen tartrate were obtained 20.88, and 25%, respectively. Release of rivastigmine from nanoparticles in the simulated gastric and body fluid during 24 h were obtained 70.5 and 79.6%, respectively, which was shown the slightly fast release of rivastigmine in simulated gastric fluid. The cytotoxicity effect of nanoparticles with and without rivastigmine was done by MTT assay on SY5Y cell lines. Results showed that the in vitro rivastigmine release from the nanoparticles containing of it exhibited the more treatment property as free rivastigmine on SY5Y.
Biomedical Image Processing / Medical Image Processing
Meysam Torabi; Emadoddin Fatemizadeh
Volume 3, Issue 3 , June 2009, , Pages 213-225
Abstract
In this paper, an MRI-based diagnosing approach has been proposed which simultaneously analyzes T1-MR and T2-MR images. The dataset contains 120 cross-sectional images of abnormal and also normal brains as control group. Due to inherent proprieties of T1 and T2 images and their principal differences, ...
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In this paper, an MRI-based diagnosing approach has been proposed which simultaneously analyzes T1-MR and T2-MR images. The dataset contains 120 cross-sectional images of abnormal and also normal brains as control group. Due to inherent proprieties of T1 and T2 images and their principal differences, particular features have been extracted from each image. Then, more meaningful data has been structured by automatically eliminating redundant data and generating a semi-linear combination of the remaining features. Considering the fact that Alzheimer's disease mainly damages the gray and white matter of the brain and knowing that these parts of the brain can be more clearly observed in T1 images, the classifier which works under a nonlinear structure, allocates more weight for processing the T1 images comparing to T2 image. The images, after being registered, have been processed in two groups of training and test sets. According to the results, three forth of the dataset which was obtained from Harvard University's dataset (The Whole Brain Atlas) has been correctly diagnosed.
