Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/516508
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dc.coverage.spatialComputer aided diagnosis of automatic skin tumour detection for clinical applications
dc.date.accessioned2023-10-07T10:23:10Z-
dc.date.available2023-10-07T10:23:10Z-
dc.identifier.urihttp://hdl.handle.net/10603/516508-
dc.description.abstractCancer is a serious consequence that arises from the uncontrolled multiplication and change in the structure of cells. These cells divide progressively forming lumps or mass of extra tissues causing a high mortality rate in humans. Skin cancer is one of the most common cancer forms which claims more than millions of precious lives every year in both men and women. According to a survey recorded by the American Institute of Cancer Research, a Melanoma skin tumour is estimated as the 19th most occurring cancer while the non-melanoma is the 5th most occurring cancer. Incident mortality rates are more than twice in men as compared to women. So, early detection of skin abnormalities becomes necessary to help expert radiologists to diagnose and treat patients effectively. Abnormal skin cells are very difficult to diagnose as they have similarities to other normal skin cells, which differ only by their compact nature and the growth of these cells.The key objective of this research work is to provide an accurate identification and an automatic classification of the cancerous skin tumour region from the Computed Tomography (CT) images in terms of region enhancement in terms of accuracy, precision, sensitivity, specificity and response time. The main focus is to estimate the accuracy of sample nodule by Computer-Aided Detection (CAD) in CT images. This novel research work will definitely help the radiologists to identify the malignant or the severe stage of skin cancer and also early-stage or benign nodules to decide the kind of treatment to be delivered to the patients newline
dc.format.extentxxii,156p.
dc.languageEnglish
dc.relationp.141-155
dc.rightsuniversity
dc.titleComputer aided diagnosis of automatic skin tumour detection for clinical applications
dc.title.alternative
dc.creator.researcherAshwini, A
dc.subject.keywordclinical applications
dc.subject.keywordComputer aided diagnosis
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.subject.keywordskin tumour
dc.description.note
dc.contributor.guideKavitha, V
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File25.7 kBAdobe PDFView/Open
02_prelim pages.pdf3.74 MBAdobe PDFView/Open
03_content.pdf693.86 kBAdobe PDFView/Open
04_abstract.pdf897.19 kBAdobe PDFView/Open
05_chapter 1.pdf1.71 MBAdobe PDFView/Open
06_chapter 2.pdf3.61 MBAdobe PDFView/Open
07_chapter 3.pdf5.94 MBAdobe PDFView/Open
08_chapter 4.pdf8.77 MBAdobe PDFView/Open
09_chapter 5.pdf6.19 MBAdobe PDFView/Open
10_chapter 6.pdf3.68 MBAdobe PDFView/Open
11_annexures.pdf6.68 MBAdobe PDFView/Open
80_recommendation.pdf1.18 MBAdobe PDFView/Open


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