Fully Automatic Detections of Abnormalities of Brain MR Images by utilizing Spatial Information and Mathematical Morphological Operators

Arshad, Javed and Wang, Yin Chai and Abdulhameed, Rakan Alenezi and Narayanan, Kulathuramaiyer (2015) Fully Automatic Detections of Abnormalities of Brain MR Images by utilizing Spatial Information and Mathematical Morphological Operators. Applied Mathematics & Information Sciences, 9 (1). pp. 213-222. ISSN 1935-0090

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Abstract

Image segmentation refers to the process of partitioning a digital image into multiple sets of pixels are known as segments. The main goal of image segmentation is to change and simplify the representation of an image into something that is more meaningful and easier to analyze. The manual transactions for segmentation by experts is a difficult phenomena and time consuming process as well as. Most of the images in the process received are lacking of good quality. The main objective of this study is to develop a reliable mechanism to enhance the image quality and extract the abnormal portion through brain MR image accurately. A spatial filter is designed by utilizing the spatial information of the image and further to use collective information to enhance the poor quality of image(s), whereas, k-means clustering and mathematical morphological operations which extract the tumor segment from images. The proposed method is applied on different types of brain MR images for both visual and quantitative evaluations. Experimental results concluded during the practicum showed promising and reliable accuracy to open a thorough research for better future perspective of the technique developed in the article. Fully Automatic Detections of Abnormalities of Brain MR Images by utilizing Spatial Information and Mathematical Morphological Operators. Available from: http://www.researchgate.net/publication/265294217_Fully_Automatic_Detections_of_Abnormalities_of_Brain_MR_Images_by_utilizing_Spatial_Information_and_Mathematical_Morphological_Operators [accessed Nov 3, 2015].

Item Type: Article
Uncontrolled Keywords: Image segmentation, Morphological operators, Spatial mask,unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, undergraduate, Postgraduate, research, Universiti Malaysia Sarawak
Subjects: T Technology > TR Photography
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 03 Nov 2015 06:49
Last Modified: 23 Feb 2017 06:40
URI: http://ir.unimas.my/id/eprint/9315

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