Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

The herbal remedy individually or in combination with standard medicines has been used in diverse medical treatises for the cure of different diseases. Pumpkin seed oil is one of the recognized edible oil and has substantial medicinal properties due to the presence of unique natural edible substances. Inflammation is an adaptive response that is triggered by noxious stimuli and conditions, which involves interactions amongst many cell types and mediators, and underlies many pathological processes. Unsaturated fatty acids (UFAs) can influence inflammation through a variety of mechanisms, and have been indicated as alternative anti-inflammatory agents to treat several inflammatory skin disorders. Pumpkin seed oil is rich in (UFAs), that its t

Background: Bell's palsy was defined as facial weakness of lower motor neuron type caused by idiopathic facial nerve involvement outside the central nervous system without evidence of aural or more widespread neurologic disease. The cause is unclear, but the disorder occurs more commonly in diabetics.Objectives: to differentiate cases of idiopathic Bell's palsy from diabetic mononeuropathy presented with Facial nerve palsy by assessing the taste, because they differ in etiology, management & prognosis.Patients &Methods: One hundred and fifteen consecutive patients were referred for the treatment of facial palsy, from May the 5th 2012 to April 12th 2013 in Al-Kindy Teaching Hospital and The Neurosciences Hospital, in Baghdad / Ira

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

The purpose of this paper is to give the condition under which every weakly closed
function is closed and to give the condition under which the concepts of weaklysemi
closed function and weakly pre-closed function are equivalent. Moreover,
characterizations and properties of weakly semi closed functions and weakly preclosed
function was given.

Background: The purpose of this study was to assess the relation among the ramal length and width with various cervical and cranio-facial measurements for a sample of Iraqi adults with different skeletal classes. Materials and method: The sample composed of 71 Iraqi adults (36 females and 35 males) with an age ranged between 17-30 years and had different skeletal mal-relations using SNA, SNB and ANB to differentiate between them and assorting them into CL.I, CL.II and CL.III mal-relation. Each individual was subjected to clinical examination and digital true lateral cephalometric radiograph that had been analyzed using AutoCAD 2007 software computer program to determine sixteen linear and ten angular measurements. Descriptive statistics wer

     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

Background: Determination of local bone mineral density (BMD) with cortical thickness and bone height may offer a comprehensive description of the bone the surgeon will encounter when he or she actually sets the implant. Quantitative computed tomography (CT) (i.e., quantitative interpretation of values derived from Hounsfield units with a suitable calibration procedure) is the modality of choice to determine BMD. The aim of the present clinical study is to determine the local bone density in dental implant recipient sites using computerized tomography. Material and method: The sample consisted of (72) Iraqi patients whom referred to Al-Kharkh General hospital, Spiral CT scan Department for bone quality and quantity assessment after one wee

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm