background : magnetic resonance imaging (mri) offers higher diagnostic accuracy for brain lesions caused by heroin abuse compared to compute tomography (ct) scan. these lesions have a low signal on t1-weighted (t1w) images and a high signal on t2-weighted (t2w) and fluid-attenuated inversion recovery (flair) images. this study aimed to evaluate the role of diffusion-weighted mri (dwi-mri) in he...

background: the goal of this study was to determine the reliability of tcd in evaluation of vertebrobasilar arteries in comparison with brain mra in patients suffering from acute vertebrobasilar stroke. methods: samples were patients with definite clinical diagnosis of vertebrobasilar stroke. for all patients brain mri, mra and tcd were performed during the first 48 hours of admission. basilar ...

detection of brain tissues using magnetic resonance imaging (mri) is an active and challenging research area in computational neuroscience. brain mri artifacts lead to an uncertainty in pixel values. therefore, brain mri segmentation is a complicated concern which is tackled by a novel data fusion approach. the proposed algorithm has two main steps. in the first step the brain mri is divided to...

#no abstract#

#no abstract#

background: accurate brain tissue segmentation from magnetic resonance (mr) images is an important step in analysis of cerebral images. there are software packages which are used for brain segmentation. these packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. thus, assessment of the quality of the segmented gray matter (gm), ...

in this paper, we present a new brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (ls-svm). the method consists of three steps. in the first two steps, the skull is removed and cerebrospinal fluid (csf) is extracted. these two steps are performed using the fast toolbox (fmrib's a...

Detection of brain tissues using magnetic resonance imaging (MRI) is an active and challenging research area in computational neuroscience. Brain MRI artifacts lead to an uncertainty in pixel values. Therefore, brain MRI segmentation is a complicated concern which is tackled by a novel data fusion approach. The proposed algorithm has two main steps. In the first step the brain MRI is divided to...

introduction septic cavernous sinus thrombosis (cst) is a rare condition that can result in high mortality and morbidity rates if not treated immediately. cst may be aseptic or septic. less common primary sites of infection include the tonsils, soft palate, middle ear, and orbit. reported cases of middle ear infection are very rare, and response to treatment is poor. conclusions findings of lab...