Fuzzy analysis of X-ray images for automated disease examination

Craig Watman*, Kim Le

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

This paper presents the design of a fuzzy decision system for Cancer and Tuberculosis detection based on X-ray lung images. The system is in a tuning stage based on advices from medical experts. With a training set of 40 positive and 10 negative images, the system can classify correctly 42% positive cases with no false negative results. This is a promising result; however the system needs further tuning with additional features and concise examination rules.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Verlag
Pages491-497
Number of pages7
ISBN (Print)9783540232063
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3214
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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