In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Summary
Background Arteriovenous malformations (AVMs) of the brain are anomalies affecting different age groups of the population, and predisposing patients to significant neurological disability from stroke, epilepsy, or other clinical manifestations. Noninvasive modalities are revealing these lesions more frequently, and with more accuracy. Previous studies on Iraqi subjects with intracranial AVMs are scarce.
Objectives The aim of the study is to correlate the CT findings of intracranial ATMs with the clinical presentations, anatomic locations, the size, and the predictable origin of the arteries feeding these lesions and their venous drainage.
Patients and Methods The charts and CT scans offifty-four Iraqi patients with an AI

Language is the realistic and sensitive basis for any communication between two or more parties. It is an important workshop that prepares meanings and coding them according to a linguistic structure governed by agreed rules that speak to and coexist with everyone.

Whereas the forms of communication are: personal, mediator and mass, none of them can move away from language in their dealings and communication patterns. Since each has its own characteristics and skills, it must be launched in its fields through verbal and non-verbal symbols and wears the elements of influential language as intended.

It makes the recipient face two things: whether he fails to understand those symbols hence its purpose fail, or he meditates s

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

Polymeric hollow fiber membrane is produced by a physical process called wet or dry/wet phase inversion; a technique includes many steps and depends on different factors (starting from selecting materials, end with post-treatment of hollow fiber membrane locally manufactured). This review highlights the most significant factors that affect and control the characterization and structure of ultrafiltration hollow fiber membranes used in different applications.    

   Three different types of polymers (polysulfone PSF, polyethersulfone PES or polyvinyl chloride PVC) were considered to study morphology change and structure of hollow fiber membranes in this review. These hollow fiber membranes were manufactured with different pro

Background:Gynecomastia and breast cancer are the two most common diseases of the male breast. Most other diseases found in male breast arise from the skin and subcutaneous tissues. Male breast cancer is relatively rare, in contrast to gynecomastia, which is relatively common.
Objectives: The aim of this report is to determine the prevalence of the different breast lesions among males; based upon the findings of fine needle aspiration cytology .
Patients and method:This study was carried out within the Main Referral Training Center for Early Detection of Breast Tumors, Medical City Teaching Hospital, Baghdad (from the
beginning of January 2003 till the end of November 2007). One hundred twenty four males&nbsp

Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

Continuous flow injection analysis (CFIA) is one of the simplest, easiest, and multilateral analytical automation methods in moist chemical analysis. This method depends on changing the physical and chemical properties of a part of the specimen spread out from the specimen injected into the carrier stream. The CFIA technique uses automatic analysis of samples with high efficiency. The CFIA PC compatibility also allows specimens to be treated automatically, reagents to be added, and reaction conditions to be closely monitored. The CFIA is one of the automated chemical analysis methods in which a successive specimen sample is to be estimated and injected into a vector stream from a flowing solution that meets the reagent and mixes at a spe