Brain tissues segmentation is usually concerned with the delineation of three types of brain matters Grey Matter (GM), White Matter (WM) and Cerebrospinal Fluid (CSF). Because most brain structures are anatomically defined by boundaries of these tissue classes, accurate segmentation of brain tissues into one of these categories is an important step in quantitative morphological study of the brain. As well as the abnormalities regions like tumors are needed to be delineated. The extra-cortical voxels in MR brain images are often removed in order to facilitate accurate analysis of cortical structures. Brain extraction is necessary to avoid the misclassifications of surrounding tissues, skull and scalp as WM, GM or tumor when implementing segmentation algorithms. In this work, two techniques have been implemented to extract the brain tissues as elementary step. The next step was utilizing the resultant skull stripped images as input of four segmentation algorithms to extract the tumor region and calculate the area value of it. The resultant skull stripped images for complete set of T2-weighted images and the adaptive K-Means clustering techniques proved the robust performance of these proposed algorithms.
Fuzzy C-means (FCM) is a clustering method used for collecting similar data elements within the group according to specific measurements. Tabu is a heuristic algorithm. In this paper, Probabilistic Tabu Search for FCM implemented to find a global clustering based on the minimum value of the Fuzzy objective function. The experiments designed for different networks, and cluster’s number the results show the best performance based on the comparison that is done between the values of the objective function in the case of using standard FCM and Tabu-FCM, for the average of ten runs.
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Image texture is an important part of many types of images, for example medical images. Texture Analysis is the technique that uses measurable features to categorize complex textures. The main goal is to extract discriminative features that are used in different pattern recognition applications and texture categorization. This paper investigates the extraction of most discriminative features for different texture images from the “Colored Brodatz” dataset using two types of image contrast measures, as well as using the statistical moments on five bands (red, green, blue, grey, and black). The Euclidean distance measure is used in the matching step to check the similarity degree. The proposed method was tested on 112 classes o
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The Specific activity of extracellular superoxide dismutase (EC-SOD) was measured in healthy persons and in patients with benign and malignant brain tumors. The results show decrease of the EC-SOD specific activity in sera of patients with benign and malignant brain tumors in comparison to that of control group.This study concentrated on studying the changes that occur in sera EC-SOD activity of patients with benign and malignant brain tumors, in comparison to that of normal individuals. The result also revealed that this isoenzyme is present in many different molecular weights forms (as judged by polyacrylamide gel electrophoresis), some of these with no enzymatic activity. Conversion among these forms occurs in the malignant sera
This study calculated the surface roughness length (Zo), zero-displacement length (Zd) and height of the roughness elements (ZH) using GIS applications. The practical benefit of this study is to classify the development of Baghdad, choose the appropriate places for installing wind turbines, improve urban planning, find rates of turbulence, pollution and others. The surface roughness length (Zo) of Baghdad city was estimated based on the data of the wind speed obtained from an automatic weather station installed at Al-Mustansiriyah University, the data of the satellite images digital elevation model (DEM), and the digital surface model (DSM), utilizing Remote Sensing Techniques. The study area w
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As result of exposure in low light-level are images with only a small number of
photons. Only the pixels in which arrive the photopulse have an intensity value
different from zero. This paper presents an easy and fast procedure for simulating
low light-level images by taking a standard well illuminated image as a reference.
The images so obtained are composed by a few illuminated pixels on a dark
background. When the number of illuminated pixels is less than 0.01% of the total
pixels number it is difficult to identify the original object.
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