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Intelligent computer aided diagnosis system for liver fibrosis / Walaa Hussein Ahmed Mohammed Elmasry ; Supervised Aboulella Oteify Hassanien , Eid Emary

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Walaa Hussein Ahmed Mohammed Elmasry , 2014Description: 101 Leaves : charts , facsimiles ; 30cmOther title:
  • نظام ذكى للمساعدة فى تشخيص تليف الكبد [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Technology Summary: Primary malignant liver tumours, cause 1.25 millions death per year worldwide. HCC is prevalent in Asia and Africa because of the presence of a large sub clinical population with hepatitis C virus infection. Early detection and accurate staging of liver cancer is an important issue in practical radiology. Although Multi Detector-row Computed Tomography ( MDCT ) or MRI is widely used for the diagnosis of liver tumours, the amount of information obtained from MDCT/MRI is very large, and its currently dif- {uFB01}cult for inexperienced radiologists or physicians to interpret all the images within a short time span. In this research, we considered the problem of developing an intelligent automated sys- tem for detecting the presence of tumour nodules in the liver CT images, that can be considered as a second reader to the radiologists. At that time and still now, it is well known that the visual detection of liver tumour nodules is a di{uFB03}cult task for radiologists, who may miss some of the nodules. Radiologists have missed these lesions due to the overlap of normal anatomic structures with nodules.
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2014.Wa.I (Browse shelf(Opens below)) Not for loan 01010110065971000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2014.Wa.I (Browse shelf(Opens below)) 65971.CD Not for loan 01020110065971000

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Technology

Primary malignant liver tumours, cause 1.25 millions death per year worldwide. HCC is prevalent in Asia and Africa because of the presence of a large sub clinical population with hepatitis C virus infection. Early detection and accurate staging of liver cancer is an important issue in practical radiology. Although Multi Detector-row Computed Tomography ( MDCT ) or MRI is widely used for the diagnosis of liver tumours, the amount of information obtained from MDCT/MRI is very large, and its currently dif- {uFB01}cult for inexperienced radiologists or physicians to interpret all the images within a short time span. In this research, we considered the problem of developing an intelligent automated sys- tem for detecting the presence of tumour nodules in the liver CT images, that can be considered as a second reader to the radiologists. At that time and still now, it is well known that the visual detection of liver tumour nodules is a di{uFB03}cult task for radiologists, who may miss some of the nodules. Radiologists have missed these lesions due to the overlap of normal anatomic structures with nodules.

Issued also as CD

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