Ameen Mohammed Abd Al-salam Selami

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• Master of Engineering
• Lecturer at University of Kirkuk

Osteoporosis is a disease that affects bones, it makes them fragile and susceptible to break. Recently, Dual-Energy X-ray Absorptiometry (DEXA) technology is being used to detect osteoporosis with low levels of radiation compared to X-Ray and CT-Scans. In this article, evaluation of the effectiveness of features extracted from DEXA images in detect...

The huge development of artificial intelligence in health care system dealing with uncertainties in the health decision-making process. The fuzzy logic provides an effective income for dealing with uncertainties. This research practices fuzzy logic (FL) system to think like an expert clinician and exam the possibility of diagnosing the risk of perf...

In this paper analysis are made to describe the effects of several types of noise on thermal image features like the Histogram, Texture, and Transform based features and compare it with regular image. The features are extracted from a bank of images before and after applying some noise bases like Gaussian, Salt & Pepper, Speckle and the Poison on t...

It is necessary to know how a camera resolution and/or its flashlight may affect the captured image properties and features, this is essential especially for those who work in the field of image processing. If the features are modified according to the mentioned two factors, they won’t be valid for processing and analysis, therefore a study should...

This paper presents a study about the features that are taken from abnormal (cancerous) brain MRI images, and how these features differ in value between the normal and the abnormal segments of the brain MRI images. The proposed algorithm depends on gathering abnormal brain MRI (axial view) images, applying some preprocessing as: Removing unnecessar...

In this paper, the effect of noise on the features of digital images has been tested. Since most of the computer and communication systems can be affected by Gaussian noise which may come from different natural sources, it was interesting to measure the effect of this noise on image features. For this purpose, a data set of several images was used...

Segmentation of brain magnetic resonance images is a crucial step in surgical and treatment planning. In this paper, a fully automatic technique is proposed for a precise segmentation of normal and pathological tissues in MRI brain images. The normal tissues such as WM (White Matter), GM (Gray Matter) and CSF (Cerebrospinal Fluid) are segmented fro...

This paper presents an intelligent classification technique to identify normal and abnormal slices of the magnetic resonance human brain images(MRI). The prtoposed hybrid technique consists of four subsequent stages; namely, dimensionality reduction, preprocessing, feature extraction, and classification. In the initial stages, the enhancement and r...