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Article
A Proposed Alzheimer's Disease Diagnosing System Based on Clustering and Segmentation Techniques

Author: Sarah J. Mohammed
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 2 Part (B) Engineering Pages: 160-165
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

lzheimer's-disease (AD) is one of the prevalent diseases that afflict theelderly. The medical field defines Alzheimer is the destruction of brain cells sothat the person loses knowledge and perception, afflict both sexes and is calleddementia. The medical field often suffers from accurate diagnosis and detection ofthe disease in the early stages. This paper presents a diagnostic approach ofAlzheimer based on K-mean clustering algorithm with Markov random fieldsegmentation on Magnetic Reasoning Images (MRI) to build software able to helpthe medical staff identifying and diagnosis the disease. The experimental resultshows that 91% accuracy is achieved, which demonstrate the system's reliabilityin the medical diagnostic environment


Article
Genetic-Based Multiresolution Noisy Color Image Segmentation

Author: Naeem Th. Yousir نعيم ثجيل يسير
Journal: AL-NAHRAIN JOURNAL FOR ENGINEERING SCIENCES مجلة النهرين للعلوم الهندسية ISSN: 25219154 / eISSN 25219162 Year: 2010 Volume: 13 Issue: 2 Pages: 167-174
Publisher: Al-Nahrain University جامعة النهرين

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Abstract

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields and make a decision of the optimum number of segmentation areas in an image when it contains similar and/or unstationary texture fields. A local novel neighborhood-based segmentation approach is proposed. Genetic algorithm is used in the proposed limited segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. The proposed system uses an adaptive threshold estimation method for image thresholding in the wavelet domain based on the Generalized Gaussian Distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quadtree is utilized to implement the fast clustering segments for multiresolution framework analysis, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results of the proposed segmentation approach are very encouraging.

تكون عملية تجزئة الصورة الملونه من اصناف مختلفة من المناطق والتي هي صلب المشكله ابداء من حساب حقول القوام المضبوطة او اعداد الاجزاء المجزئة بصورة كفوءةعندما تتالف الصورة من حقلية متشابهةاستخدمت الخوارزمية المثالية لطريقة التجزئه الكفؤة المقترحة ثم ساب دالة الطاقة والتي تعرف باعتمادها تقليل حقول (Markov) العشوائية ثم استخدام طريقة استخراج التدرج العتبي لتدرج الصورة في اطياف الموجيات (wavelet) والتي استندت على نمذجة توزيع (Gaussian) العامة تسمى هذه الطريقة ( بالتقلص الطبيعي) والتي هي طريقة كفوءة حسابيا ومتدرجة بسبب ان العوامل المطلوبه لحسابها قد اعتمدت على اطياف موجية لها طاقة فرعية والتي استخدمت في مرحلة ماقبل التجزئة.تم استخدام الشجرة الرباعية (quadtree) لتفيذ العمل متعدد الدقة والذي يمكن من استخدام ستراتيجيات مختلفة بمستويات دقه مختلفه. كذلك ان العملية الحسابيه بالامكان تسريعها ان النتائج المستحصلة من هذا البحث قد بينت بان هذه الطريقة هي طريقة مشجعة للدخول بها.


Article
Genetic-Based Multiresolution Noisy Color Image Segmentation

Author: Naeem Th. Yousir
Journal: Journal of Baghdad College of Economic sciences University مجلة كلية بغداد للعلوم الاقتصادية الجامعة ISSN: 2072778X Year: 2008 Issue: 18 Pages: 319-335
Publisher: Baghdad College of Economic Sciences كلية بغداد للعلوم الاقتصادية

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Abstract

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum number of segmentation areas in an image when it contains similar and/or unstationary texture fields. A novel neighborhood-based segmentation approach is proposed. Genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper uses an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quadtree is employed to implement the multiresolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

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