Fuzzy analysis of X-ray images for automated disease examination

dc.contributor.authorWatman, Craigen
dc.contributor.authorLe, Kimen
dc.date.accessioned2025-12-31T18:41:34Z
dc.date.available2025-12-31T18:41:34Z
dc.date.issued2004en
dc.description.abstractThis 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.en
dc.description.statusPeer-revieweden
dc.format.extent7en
dc.identifier.isbn9783540232063en
dc.identifier.issn0302-9743en
dc.identifier.scopus33745315185en
dc.identifier.urihttps://hdl.handle.net/1885/733797741
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.subjectComputerised medical repositoryen
dc.subjectData miningen
dc.subjectFuzzy systemen
dc.subjectImage segmentationen
dc.subjectPattern recognitionen
dc.titleFuzzy analysis of X-ray images for automated disease examinationen
dc.typeBook chapteren
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage497en
local.bibliographicCitation.startpage491en
local.contributor.affiliationWatman, Craig; School of Engineering, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationLe, Kim; University of Canberraen
local.identifier.ariespublicationU3488905xPUB10323en
local.identifier.doi10.1007/978-3-540-30133-2_64en
local.identifier.essn1611-3349en
local.identifier.pure443d0c9e-0e5a-433a-9aae-75d539d7ff09en
local.identifier.urlhttps://www.scopus.com/pages/publications/33745315185en
local.type.statusPublisheden

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