Myocardium rotation and torsion are important indicators of the cardiac function. Currently, tagged Magnetic Resonance Imaging (tMRI) sequences are analyzed to estimate these parameters. Unfortunately, tMRI is not widely used in clinical practice because it prolongs the scanning time and requires sophisticated analysis software. In this work, we present a method for estimating the myocardium rotation from standard cine MRI sequences. The method is based on identifying special features, i.e. landmarks, of the intensity pattern around the myocardium borders at each timeframe. Each set of

Tagged Magnetic Resonance (MR) images are considered the gold standard for evaluating the cardiac regional function. Nevertheless, the low myocardium-to-blood contrast in tagged MR images prevents accurate segmentation of the myocardium, and hence, hinders the quantitative assessment of the global function of the heart. In this work, a method for enhancing the myocardium-to-blood contrast in tagged MR images is proposed. First, the tag pattern in each input tagged MR image is removed using technique based on the image texture and the frequency components of the tag pattern to produce two

The strain encoding (SENC) technique directly encodes regional strain of the heart into the acquired MR images and produces two images with two different tunings so that longitudinal strain, on the short-axis view, or circumferential strain on the long-axis view, are measured. Interleaving acquisition is used to shorten the acquisition time of the two tuned images by 50%, but it suffers from errors in the strain calculations due to inter-tunings motion of the heart. In this work, we propose a method to correct for the inter-tunings motion by estimating the motion-induced shift in the spatial

Stimulated echo acquisition mode (STEAM) is a generic imaging technique that lies at the core of many magnetic resonance imaging (MRI) techniques such MRI tagging, displacement encoded MRI, black-blood cardiac imaging. Nevertheless, tissue deformation causes frequency shift of the MR signal and leads to severe signal attenuation. In this work, a maximum likelihood estimator for the signal amplitude is proposed and used to correct the image artifacts. Numerical simulation and real MR data are used to test and validate the proposed method. © 2011 IEEE.

In the last few years the gene expression microarray technology has become a central tool in the field of functional genomics in which the expression levels of thousands of genes in a biological sample are determined in a single experiment. Several clustering and biclustering methods have been introduced to analyze the gene expression data by identifying the similar patterns and grouping genes into subsets that share biological significance. However, it is not clear how the different methods compare with each other with respect to the biological relevance of the biclusters and clusters as well

Membrane computing is a computational framework that depends on the behavior and structure of living cells. P systems are arising from the biological processes which occur in the living cells’ organelles in a non-deterministic and maximally parallel manner. This paper aims to build a powerful computational model that combines the rules of active and mobile membranes, called Mutual Dynamic Membranes (MDM). The proposed model will describe the biological mechanisms of the metabolic regulation of mitochondrial dynamics made by mitochondrial membranes. The behaviors of the proposed model regulate

The Learning process in education systems is one of the most important issues that affect all societies. Advances in technology have influenced how people communicate and learn. Gaming Techniques (GT) and Augmented Reality (AR) technologies provide new opportunities for a learning process. They transform the student’s role from passive to active in the learning process. It can provide a realistic, authentic, engaging and interesting learning environment. Hand Gesture Recognition (HGR) is a major driver in the field of Augmented Reality (AR). In this paper, we propose an initiative Augmented

Nile tilapia, Oreochromis niloticus, is the principal fish bred in Egypt. A pilot study was designed to analyze the bacterial composition of the Nile tilapia fish guts from two saltwater lakes in Northern Egypt. Fish samples were obtained from two Delta lakes: Manzala (ML) and Borollus (BL). DNA was extracted, and the bacterial communities in the stomach content were classified (down to the species level) using the 16S rRNA-based analysis. From the two metagenomics libraries in this study, 1,426,740 reads of the amplicon sequence corresponding to 508 total taxonomic operational units were

Infection with multiple drug resistant (MDR) Escherichia coli poses a life threat to immunocompromised pediatric cancer patients. Our aim is to genotypically characterize the plasmids harbored in MDR E. coli isolates recovered from bacteremic patients of Children’s Cancer Hospital in Egypt 57357 (CCHE 57357). In this study, 21 carbapenem-resistant E. coli (CRE) isolates were selected that exhibit Quinolones and Aminoglycosides resistance. Plasmid shot-gun sequencing was performed using Illumina next- generation sequencing platform. Isolates demonstrated resistant to all beta-lactams

neurodegenerative diseases have complex pathological mechanisms. Detecting disease-associated genes with typical differentially expressed gene selection approaches are ineffective. Recent studies have shown that wrappers Evolutionary optimization methods perform well in feature selection for high dimensional data, but they are computationally costly. This paper proposes a simple method based on a genetic algorithm engaged with the Empirical Bays T-statistics test to enhance the disease-associated gene selection process. The proposed method is applied to Affymetrix microarray data from