header
Image from OpenLibrary

A 3D reconstruction of pulmonary nodules from 2D CT images computer aided diagnosis based system / Ayat Motawakkel Karrar Ahmed ; Supervised Manal Abdelwahed , Mai Said Mabrouk

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ayat Motawakkel Karrar Ahmed , 2021Description: 102 P. : charts , facsimiles ; 30cmOther title:
  • بناء أورام الرئة ثلاثية الأبعاد من الصور المقطعية ثنائية الأبعاد اعتمادا على نظام تشخيص الحاسب الآلى [Added title page title]
Subject(s): Available additional physical forms:
  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: Lung cancer is one of the most serious cancers in the world with the minimum survival rate. Lung nodules may be isolated from (solitary) or attached to (juxtapleural) other. In this paper a Computer Aided Diagnosis system is proposed to classify between solitary nodule and juxtapleural nodule inside the lungs.Two main auto-diagnostic schemes of supervised learning for classification are achieved.Three segmentation approaches are proposed.The three classifiers of the first scheme are K-Nearest Neighborhood, Artificial Neural Network and Support Vector Machine. In the second scheme, Deep Convolutional neural networksare used. Because of limited data sample and imbalanced data, 10-fold cross validation and random oversampling are used.The 3D reconstruction of pulmonary nodules based on the surface rendering technique and visualization by 3D slicer are achieved
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2021.Ay.A (Browse shelf(Opens below)) Not for loan 01010110084851000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2021.Ay.A (Browse shelf(Opens below)) 84851.CD Not for loan 01020110084851000

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Lung cancer is one of the most serious cancers in the world with the minimum survival rate. Lung nodules may be isolated from (solitary) or attached to (juxtapleural) other. In this paper a Computer Aided Diagnosis system is proposed to classify between solitary nodule and juxtapleural nodule inside the lungs.Two main auto-diagnostic schemes of supervised learning for classification are achieved.Three segmentation approaches are proposed.The three classifiers of the first scheme are K-Nearest Neighborhood, Artificial Neural Network and Support Vector Machine. In the second scheme, Deep Convolutional neural networksare used. Because of limited data sample and imbalanced data, 10-fold cross validation and random oversampling are used.The 3D reconstruction of pulmonary nodules based on the surface rendering technique and visualization by 3D slicer are achieved

Issued also as CD

There are no comments on this title.

to post a comment.