Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement, patients were imaged with sagittal short tau inversion recovery sequences and sagittal T2 weighted. Results: The mean age of the patients was 32.5 ± 6.7years; female to male ratio was 2.7:1. The total number of spinal cord MS lesions was 44 of them 86.4% in the cervical spine, 68.2%of the lesions had less than one vertebra extension,79.6% of the lesions did not show changes in the spinal cord morphology. There was a significant upgrading in the lesions conspicuity at short tau inversion recovery sequence comparing to T2 weighted image, P<0.001. A significant difference had been found in artifact grading between both sequences; P<0.001. Conclusions: short tau inversion recovery magnetic resonance image sequences improve detection of MS spinal cord plaques compared with T2 weighted image and itincreasesthe conspicuity of the visualized T2weighted image lesions, but also it accentuates theartifacts more than T2weighted image.
The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di
... Show MoreThe recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
... Show More In this research, an adaptive Canny algorithm using fast Otsu multithresholding method is presented, in which fast Otsu multithresholding method is used to calculate the optimum maximum and minimum hysteresis values and used as automatic thresholding for the fourth stage of the Canny algorithm. The new adaptive Canny algorithm and the standard Canny algorithm (manual hysteresis value) was tested on standard image (Lena) and satellite image. The results approved the validity and accuracy of the new algorithm to find the images edges for personal and satellite images as pre-step for image segmentation.
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
A computational investigation has been carried out to describe synthesis optimization procedure of magnetic lenses. The research is concentrated on the determination of the inverse design of the symmetrical double polepiece magnetic lenses whose magnetic field distribution is already defined. Magnetic lenses field model well known in electron optics have been used as the axial magnetic field distribution. This field has been studied when the halfwidth is variable and the maximum magnetic flux density is kept constant. The importance of this research lies in the possibility of using the present synthesis optimization procedure for finding the polepieces design of symmetrical double polepiece magnetic lenses which have the best proje
... Show MoreDue to a party's violation of his obligations or responsibilities indicated in the contract, many engineering projects confront extensive contractual disputes, which in turn need arbitration or other forms of dispute resolution, which negatively impact the project's outcome. Each contract has its terms for dispute resolution. Therefore, this paper aims to study the provisions for dispute resolution according to Iraqi (SBDW) and the JCT (SBC/Q2016) and also to show the extent of the difference between the two contracts in the application of these provisions. The methodology includes a detailed study of the dispute settlement provisions for both contracts with a comparative analysis to identify the differences in the appli
... Show MoreThe partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of are derived from the relation between and level density parameter . The formulae used to derive are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on from the Thomas-Fermi formula show a good agreement with the experimental data.
Steel-concrete-steel (SCS) structural element solutions are rising due to their advantages over conventional reinforced concrete in terms of cost and strength. The impact of SCS sections with various core materials on the structural performance of composites has not yet been fully explored experimentally, and in this work, both slag and polypropylene fibers were incorporated in producing eco-friendly steel-concrete-steel composite sections. This study examined the ductility, ultimate strength, failure modes, and energy absorption capacities of steel-concrete-steel filled with eco-friendly concrete, enhanced by polypropylene fiber (PPF) to understand its impact on modern structural projects. Eco-friendly concrete was produced by the partial
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