Fuzzy analysis of X-ray images for automated disease examination

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Watman, Craig
Le, Kim

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Springer Verlag

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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.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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