Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

Background: Ultrasound is a valuable tool for evaluating fetal problems throughout pregnancy. Amniotic fluid anomalies have been associated with unfavorable maternal, fetal, and obstetrical outcomes. Objective: To determine the effect of echogenic amniotic fluid during term pregnancy on the presence of meconium stain liquor and pregnancy outcome. Methods: A cross-sectional study was conducted on 1080 term pregnant women who visited Al-Elwiya Maternity Teaching Hospital from May 1st, 2021, to May 1st, 2023. Ultrasound was used to analyze echogenic amniotic fluid and turbid liquor. The liquor state was tested either after an artificial membrane rupture in the vaginal delivery trial or during a cesarean section. Results: Echogenic amni

According to the prevalence of multidrug resistance bacteria, especially Pseudomonas aeruginosa, in which the essential mechanism of drug resistance is the ability to possess an efflux pump by which extrusion of antimicrobial agents usually occurs, this study aims to detect the presence of mexB multidrug efflux gene in some local isolates of this bacteria that show resistance towards three antibiotics, out of five. Sensitivity test to antibiotics was performed on all isolates by using meropenem (10μg/disc), imipenem (10μg/disc), amikacin (30 μg/disc), ciprofloxacin (5μg/disc) and ceftazidime (30 μg/disc). Conventional PCR results showed the presence of mexB gene (244bp) in four isolates out of ten (40%). In addition,25, 50μg/ml of cur

Introduction The abortions reasons in several circumstances yet are mysterious, nevertheless the bacterial toxicities signify a main reason in abortion, where germs seems to be the utmost elaborate pathogens (Khameneh et.al., 2014) and (Oliver and Overton ,2014). Between numerous germs, Humano

The research aims to identify the importance of using analytical procedures in the detection of creative accounting practices. To achieve this goal, (100) questionnaires were prepared and distributed to the auditors in the Federal Financial Supervision Bureau and the authorized auditors' offices and practitioners of the auditing profession in Iraq. For the purpose of testing the research hypothesis and analyzing data, some appropriate statistical methods have been used and the use of the statistical program (SPSS) to analyze the data. The results of the research showed that the analytical procedures and tests applied by the auditor have a role in revealing and limiting creative accounting practices and methods and that auditors u

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff