Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.

This study was aimed to investigate the association between thyroid disorder and Helicobacter pylori infection in 122 patients (100 females and 22 males )and for comparison, 60 healthy individuals (31females and 29 males),who had no thyroid disorder, were also included in the study. Blood samples were collected from both patients and the healthier individuals. Enzyme Linked Fluorescent Assay (ELFA) technique through using Vitek Immuno Diagnostic Assay System (VIDAS) was applied to measure levels of the thyroid hormones (tri-iodothyronine T3, tetra-iodothyroxine T4) and thyroid stimulating hormone (TSH). From the results obtained, patients were classified into three groups: 40 were

The study aims to demonstrate the importance of instructional methods in teaching Arabic language as a second language or teaching the Arabic language to non-native speakers. The study is in line with the tremendous development in the field of knowledge, especially in the field of technology and communication, and the emergence of many electronic media in education in general and language teaching in particular. It employs an image in teaching vocabulary and presenting the experience of the Arabic Language Institute for Non-Speakers-King Abdul-Aziz University. The study follows the descriptive approach to solve the problem represented by the lack of interest in the educational methods when teaching Arabic as a second language. Accordingl

This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).