Automatic expert diagnostic system in CRC

Other Title(s)

نظام متخصص لتشخيص سرطان القولون

Dissertant

al-Muharib, Hibah Ahmad Salasi

Thesis advisor

Hasan, Qays
Tidmuri, Sarah

Comitee Members

al-Zubi, Muhammad
Khasawinah, Baha al-Din
Jasir, Edward

University

Princess Sumaya University for Technology

Faculty

King Hussein Faculty for Computing Sciences

Department

Department of Computer Sciences

University Country

Jordan

Degree

Master

Degree Date

2016

English Abstract

This research implements an automatic expert diagnostics system that employs medical image processing to improve early colon cancer detection via machine learning.

The process includes a four-step algorithm in order to achieve the objectives addressed in this research.

These steps are performed automatically by the system where it has been trained and tested by supervised pre-determined parameters.

The system successfully achieved 88.4 percent sensitivity for polyps greater than 6mm in size with less than two false positive per case.

The system has been tested against other work and using different number of polyps, where it recorded a successful classification for 92 polyps out of 104, over an average testing of ten times.

Main Subjects

Information Technology and Computer Science

No. of Pages

63

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-693729