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White Matter Hyperintensities (WMHs) are suspected to be a direct manifestation of microvascular ischemic injury in the distribution of the penetrating arteriolar vessels on magnetic resonance imaging (MRI) and usually seen in elderly persons. Further study on this issue is important as it might relate to other diseases. Early detection might be able to prolong brain health in people and prevent the...
Automated MRI segmentation techniques are helpful for a physician for early diagnosis of degenerating diseases in individual patients. Here we are using the T1weighted axial MR images of neuro degenerative diseases. The assessment of the accuracy of the result is done by an expert. FCM an unsupervised clustering technique is implemented in order to classify the brain voxel. The brain voxels are classified...
Brain tissue segmentation of MRI helps in the possibility of improved clinical decision making and diagnosis, and it also gives a new insight into the mechanism of the disease. Manual interaction is time consuming and it may be bias and variable. We have developed an automatic segmentation algorithm for brain MRI using Artificial Neural Network (ANN) technique. The contribution of this work is an...
A standard segmentation problem within Magnetic Resonance Imaging (MRI) is the task of labelling voxels according to their tissue type that are White Matter (WM), Gray Matter (GM), and Cerebrospinal fluid (CSF).Image segmentation provides volumetric quantification of cortical atrophy and thus helps in the diagnosis of degenerative diseases such as Epilepsy, Schizophrenia, Alzheimer's disease, Dementia...
At its simplest, volume calculation of MR Image segmented & further soft computed to estimate the affected intensity of Alzheimer's disease is dealt with this paper. It is concerned with Voxel Based Morphometry to render the first part segmentation. The result gives an active region which further needs an estimation to justify the diagnosis. As in this case the image is in form of voxels. When...
In the field of quantitative imaging, the creation of accurate volumes of interest (VOIs) is often of central importance. However, the process of creating these VOIS for multiple subjects can be time-intensive and there are many chances to introduce variability on inter- and intra-investigator levels. Although previous work has shown that image normalization through cortical surface mapping can be...
As described herein, we propose an unsupervised method for segmentation of magnetic resonance (MR) brain images by hybridizing the self-mapping characteristics of 1-D Self-Organizing Maps (SOMs) and using incremental learning functions of fuzzy Adaptive Resonance Theory (ART). The proposed method requires no operator to specify the representative points. Nevertheless, it can segment tissues (such...
Brain development has become a prominent issue in recent years. In people with or without any visible or invisible diseases, degeneration is an inevitable phenomenon that a brain will develop over time. Diffusion Tensor Image (DTI) has been a robust technique to observe white matter details in normal subjects and in patients. In this study, our goal is to consolidate DTI indices to properly differentiate...
Computer-assistance has reached virtually every domain within the field of medical imaging. But, even after four decades of intensive medical image analysis research, most of the fully automated methods have not been adopted for clinical routine use. Dedicated computer aided-diagnosis tools with proven clinical impact exist for a narrow range of applications, including mammography and chest imaging,...
In this study, the white matter, gray matter and the tissues affected by Multiple Sclerosis are segmented semi-automatically from Magnetic Resonance images using programming environments ITK (Insight Registration and Segmentation Toolkit), VTK (Visualization Toolkit) and MeVisLab (Medical Image Processing and Visualization).
In this study, we are proposing a novel nonlinear classification approach to discriminate between Alzheimer's Disease (AD) and a control group using T1-weighted and T2-weighted Magnetic Resonance Images (MRI's) of brain. Since T1-weighted images and T2-weighted images have inherent physical differences, obviously each of them has its own particular medical data and hence, we extracted some specific...
We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inference algorithms rely on pairwise registrations between the test image and individual training images. The training labels are then transferred to the test image and fused to compute the final segmentation of the test subject...
The way that Alzheimer's disease (AD) invades brain is to destroy its fundamental elements, i.e. neurons. The phenomenon of neuron destruction reflects volume changes on brain tissues such as gray matter, white matter and cerebro-spinal fluid. In the AD-related research, the volumetric analysis of hippocampus is the most extensive study. However, the segmentation and identification of the hippocampus...
Diffusion Tensor Imaging (DTI) and tractography are able to model fiber architecture within the white matter and become a major component of clinical neuroradiology. The challenge is to answer neuro-anatomic questions by using group studies. In some diseases, the asymmetry between involved tracts is expected to be greater than that in controls. If the quantitative detection of asymmetry is sufficiently...
The propagation of shear waves in soft tissue can be visualized by magnetic resonance elastography (MRE) to characterize tissue mechanical properties. Dynamic deformation of brain tissue arising from shear wave propagation may underlie the pathology of blast-induced traumatic brain injury. White matter in the brain, like other biological materials, exhibits a transversely isotropic structure, due...
When using low power laser in therapy and diagnostics, the knowledge about the relationship between laser wavelengths and the percentage of reflected energy in the interface air-tissue and the distribution of energy in tissue helps us to choose appropriate wavelengths. In this paper, we present some results obtained from the simulation of low power 633, 780, 850, and 940 nm laser in brain by Monte...
Alzheimer's disease (AD) is characterized by progressive cognitive deterioration together with declining activities of daily living and neuropsychiatric symptoms. It is the most common cause of dementia. It is recognized that the production and maintenance of myelin is essential for normal brain function. Aging-related breakdown of myelin negatively impacts the cognitive performances with the neurofibrilary...
The aim of this study is to investigate abnormalities in the brain tissue of patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS). In this method, magnetization transfer ratio (MTR) parameter accompanied with segmentation regional measurements and histogram analysis were used to improve the evaluation of disease progression in CIS patients. Conventional MR imaging...
The aim of this study is to investigate abnormalities and characterize pathologic changes associated with demyelination in the brain tissue of patients with multiple sclerosis (MS). In this method, magnetization transfer parameters such as magnetization transfer ratio (MTR), magnetization transfer rate (Ksat) and native relaxation time of brain tissue with and without applying saturation pulse were...
Tinnitus is defined as an unwanted auditory perception of internal origin, usually localized, and rarely heard by others. Persisting appearances of tinnitus are most commonly combined with diseases or damage in the inner ear or neuro-auditory pathway. Diffusion tensor magnetic resonance imaging (DTI) is a new imaging method with the capability of providing non-invasive information on tissue microstructure...
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