Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/337658
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dc.date.accessioned2021-08-25T04:06:01Z-
dc.date.available2021-08-25T04:06:01Z-
dc.identifier.urihttp://hdl.handle.net/10603/337658-
dc.description.abstractThe most common cause of death in the world is lung cancer. Lung newlinecancer is considered a remarkable cancer because it requires more than one million newlinelives a year. Lung cancer mortality rates are the most striking among other types of newlinetumors. The survival of pulmonary disease is determined especially with its newlineprogression at the time of recognition . Early recognition of cancer can help to cure newlinethe disease completely. Requiring early recognition of cancer is important. Early newlinerecognition of lung cancer is the most encouraging way to reduce the risk of newlinesurvival. The cancer stage in its study is a key predictor of survival and it defines newlinetreatment. There are different cancer recognition techniques in the literature, but newlinemost techniques do not provide significant recognition accuracy. A variety of newlineimaging modalities have been proposed to detect lung cancer. Computed newlineTomography (CT) is the most commonly used imaging technique newline
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dc.languageEnglish
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dc.rightsuniversity
dc.titleA Novel Dlionabc Segmentation and Feature Selection Approach for Lung Cancer Recognition on CT Images Based on ICNN Classification
dc.title.alternative
dc.creator.researcherAsuntha A
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Mechanical
dc.description.note
dc.contributor.guideAndy Srinivasan
dc.publisher.placeKattankulathur
dc.publisher.universitySRM University
dc.publisher.institutionDepartment of Mechanical Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Mechanical Engineering

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certificate page.pdf52.73 kBAdobe PDFView/Open
chapter 1.pdf224.84 kBAdobe PDFView/Open
chapter 2.pdf118.22 kBAdobe PDFView/Open
chapter 3.pdf896.65 kBAdobe PDFView/Open
chapter 4.pdf583.17 kBAdobe PDFView/Open
chapter 5.pdf771.26 kBAdobe PDFView/Open
chapter 6.pdf661.01 kBAdobe PDFView/Open
chapter 7.pdf308.73 kBAdobe PDFView/Open
chapter 8.pdf50.15 kBAdobe PDFView/Open
list of publications.pdf20.73 kBAdobe PDFView/Open
preliminary pages.pdf93.17 kBAdobe PDFView/Open
references.pdf77.59 kBAdobe PDFView/Open
title page.pdf565.96 kBAdobe PDFView/Open
vitae.pdf20.36 kBAdobe PDFView/Open


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