Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.
One of the most important phenomenon that occurs in sheet metal forming processes is the spring-back, which causes several geometrical alterations in the parts. The accurate prediction of springback after bending unloading is the key to the tool design, operation control, and precision estimate concerning the part geometry. This study investigated experimentally the effect of pretension in three rolling direction (0, 90, 45 degree) on the springback behavior of the yellow brass, sheet under V shape bending die. The pre-tension ranges from five different levels starting of 11% to 55% from the total strain in each rolling direction by regular increase of 11 %, then bent on a V-die 90 degree for the springback estimate. From experiment the
... Show MoreLoss of drilling fluid in the Nasiriyah oil field can be considered as a big,
serious, and expensive problem at the same time, therefore accurate and integrated
program must be prepared before start drilling in layers that are likely to get loss
circulation. From the available data of well Ns-13, the area of loss was detected in
five layers, which are Dammam, Um- radoma, Tayarat, Shiranish and Hartha since
these layers contain natural cracks and high porosity represented by vugs.
Methods of prevention have been identified by specifying the minimum values
of drilling parameters to reduce hydrostatic pressure, thus reducing equivalent
density of drilling mud during the circulation, depths of casing shoes is
deter
The childhood is an important stage in building the character of the individual and where children acquire the most important experiences . providing proper growth requirements of the things follows assist them in achieving a stable and together Childhood is the violence of indicators that can determine whether personal or illness social .the social circumstances experienced community Iraqi and continues through crises successive wars and explosions and the displacement and that these events may lead to changes in the social behavior of individuals and may contribute to the spread of violence in Iraqi society and observed various forms in (home, school, street, and work), so it was natural that a child the first affected by these waves o
... Show MoreWith its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
... Show MoreBackground/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MoreSegmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology
... Show MoreDigital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
... Show MoreTwo 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.