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Alzheimer detection using Gaussian MAP descriptors / Shereen Ekhlas Mohammed Ibrahim ; Supervised Ayman Mohammed Eldeib , Inas Ahmed Yassine

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Shereen Ekhlas Mohammed Ibrahim , 2018Description: 66 P. : charts , facsimiles ; 30cmOther title:
  • تشخيص مرض الزهايمر باستخدام خرائط جاوس [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: Alzheimer{u2019}s disease (AD) is a considered one of the common elderly disease that causes changes in behavioral and memory loss because of the death of brain cells. There are three stages for Alzheimer disease named: Alzheimer{u2019}s Disease patient (AD), Mild cognitive impairment (MCI) and Early stage. In this work, we purpose the use of the Gaussian map descriptors to distinguish between AD, MCI and normal (N) subjects, by analyzing the hippocampus and amygdala. Based on Gaussian maps, several features were extracted such as the Gaussian curvatures, the mean curvature and Gaussian shape operator, which are then fed to the Support Vector Machine (SVM) in order to employ the classification task. The proposed workflow consists of seven main steps: Eddy current correction, Brain extraction, registration, segmentation, Gaussian map features calculations, and evaluation and validation of results. This thesis gives a detailed implementation for each mentioned steps
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2018.Sh.A (Browse shelf(Opens below)) Not for loan 01010110075412000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2018.Sh.A (Browse shelf(Opens below)) 75412.CD Not for loan 01020110075412000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Alzheimer{u2019}s disease (AD) is a considered one of the common elderly disease that causes changes in behavioral and memory loss because of the death of brain cells. There are three stages for Alzheimer disease named: Alzheimer{u2019}s Disease patient (AD), Mild cognitive impairment (MCI) and Early stage. In this work, we purpose the use of the Gaussian map descriptors to distinguish between AD, MCI and normal (N) subjects, by analyzing the hippocampus and amygdala. Based on Gaussian maps, several features were extracted such as the Gaussian curvatures, the mean curvature and Gaussian shape operator, which are then fed to the Support Vector Machine (SVM) in order to employ the classification task. The proposed workflow consists of seven main steps: Eddy current correction, Brain extraction, registration, segmentation, Gaussian map features calculations, and evaluation and validation of results. This thesis gives a detailed implementation for each mentioned steps

Issued also as CD

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