Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Expert System with an Embedded Imaging Module for Diagnosing Lung Diseases

Devan, Kavitha Shaga (2006) Expert System with an Embedded Imaging Module for Diagnosing Lung Diseases. Masters thesis, Universiti Teknologi Petronas.

[img] PDF
Download (6Mb)

Abstract

Lung diseases are one of the major causes of suffering and death in the world. Improved survival rate could be obtained if the diseases can be detected at its early stage. Specialist doctors with the expertise and experience to interpret medical images and diagnose complex lung diseases are scarce. In this work, a rule-based expert system with an embedded imaging module is developed to assist the general physicians in hospitals and clinics to diagnose lung diseases whenever the services of specialist doctors are not available. The rule-based expert system contains a large knowledge base of data from various categories such as patient's personal and medical history, clinical symptoms, clinical test results and radiological information. An imaging module is integrated into the expert system for the enhancement of chest X-Ray images. The goal of this module is to enhance the chest X-Ray images so that it can provide details similar to more expensive methods such as MRl and CT scan. A new algorithm which is a modified morphological grayscale top hat transform is introduced to increase the visibility of lung nodules in chest X-Rays. Fuzzy inference technique is used to predict the probability of malignancy of the nodules. The output generated by the expert system was compared with the diagnosis made by the specialist doctors. The system is able to produce results which are similar to the diagnosis made by the doctors and is acceptable by clinical standards.

Item Type: Thesis (Masters)
Academic Subject : Academic Department - Electrical And Electronics - Instrumentation and Control - Intelligent System - Imaging in intelligent surveillance systems
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 30 Sep 2013 16:55
Last Modified: 25 Jan 2017 09:46
URI: http://utpedia.utp.edu.my/id/eprint/8044

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...