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dc.contributor.authorAzian Azamimi, Abdullah-
dc.contributor.authorHasdiana, Mohamaddiah-
dc.date.accessioned2012-04-10T08:31:31Z-
dc.date.available2012-04-10T08:31:31Z-
dc.date.issued2010-11-30-
dc.identifier.citationp. 138-143en_US
dc.identifier.isbn978-1-4244-7600-8-
dc.identifier.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5742216-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/18750-
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.org/en_US
dc.description.abstractLung cancer is the most common of lethal types of cancer. One of the most important and difficult tasks a doctor has to carry out is the detection and diagnosis of cancerous lung nodules from x-ray image's result. Some of these lesions may not be detected because of camouflaged by the underlying anatomical structure, the low-quality of the images or the subjective and variable decision criteria used by doctors. Hence, a detection system using cellular neural network (CNN) is developed in order to help the doctors to recognize the doubtful lung cancer regions in x-ray films. In this study, a CNN algorithm for detecting the boundary and area of lung cancer in x-ray image has been proposed. Computer simulation result shows that our CNN algorithm is verified to detect some key lung cancer symptoms successfully and has been proved by radiologist.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofseriesProceedings of the IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010en_US
dc.subjectLung canceren_US
dc.subjectCellular neural networksen_US
dc.subjectX-ray filmsen_US
dc.subjectImage processingen_US
dc.titleDevelopment of cellular neural network algorithm for detecting lung cancer symptomsen_US
dc.typeWorking Paperen_US
dc.contributor.urlazamimi@unimap.edu.myen_US
dc.contributor.urls061150177@unimap.edu.myen_US
Appears in Collections:Conference Papers
Azian Azamimi Abdullah

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