header
Image from OpenLibrary

Development of pathological microscopic cad systembased on advanced computing and deep learning / Ahmed Ismail Mohamed Mahdy Shahin ; Supervised Amr Sharawy , Khalid Mohamed Amin

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Ismail Mohamed Mahdy Shahin , 2018Description: 111 P. : charts , facsimiles ; 30cmOther title:
  • تطوير أنظمة التشخيص الميكروسكوبى الآلى للأمراض استنادا إلى طرق الحوسبة المتقدمة و التعليم العميق [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 System and Biomedical Engineering Summary: In this thesis, three different approaches are proposed for increasing the automated cell morphology equipment performance. The first is based on the traditional medicalCAD system approach, the second is based on deep learning approach, and the third is basedon fusion of two previous approaches. The traditional pathological CAD system is developed in multi-dimensions through neutrosophic sets and GPU. A novel deep learning architecture is proposed to classifiy cells.The experimental results demonstrate that the proposed techniques arepromising with low complexity, adaptive and more robustness. This provides the basis for automatic medical diagnosis and further processing of medical images
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.2018.Ah.D (Browse shelf(Opens below)) Not for loan 01010110075677000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2018.Ah.D (Browse shelf(Opens below)) 75677.CD Not for loan 01020110075677000

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

In this thesis, three different approaches are proposed for increasing the automated cell morphology equipment performance. The first is based on the traditional medicalCAD system approach, the second is based on deep learning approach, and the third is basedon fusion of two previous approaches. The traditional pathological CAD system is developed in multi-dimensions through neutrosophic sets and GPU. A novel deep learning architecture is proposed to classifiy cells.The experimental results demonstrate that the proposed techniques arepromising with low complexity, adaptive and more robustness. This provides the basis for automatic medical diagnosis and further processing of medical images

Issued also as CD

There are no comments on this title.

to post a comment.