Intelligent computer aided diagnosis system for liver fibrosis /
Walaa Hussein Ahmed Mohammed Elmasry
Intelligent computer aided diagnosis system for liver fibrosis / نظام ذكى للمساعدة فى تشخيص تليف الكبد Walaa Hussein Ahmed Mohammed Elmasry ; Supervised Aboulella Oteify Hassanien , Eid Emary - Cairo : Walaa Hussein Ahmed Mohammed Elmasry , 2014 - 101 Leaves : charts , facsimiles ; 30cm
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- 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 dicult 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.
CAD System Image Segmentation Liver Fibrosis
Intelligent computer aided diagnosis system for liver fibrosis / نظام ذكى للمساعدة فى تشخيص تليف الكبد Walaa Hussein Ahmed Mohammed Elmasry ; Supervised Aboulella Oteify Hassanien , Eid Emary - Cairo : Walaa Hussein Ahmed Mohammed Elmasry , 2014 - 101 Leaves : charts , facsimiles ; 30cm
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- 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 dicult 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.
CAD System Image Segmentation Liver Fibrosis