Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/598158
Title: A deep learning approach to improve detectionandclassificationofbraintumorinmriimages
Researcher: swetha v
Guide(s): CH RENUMADHAVI
Keywords: Engineering
Engineering and Technology
Engineering Biomedical
University: Visvesvaraya Technological University, Belagavi
Completed Date: 2023
Abstract: Brain tumor is considered as one of the most lethal state in cancer where medicalimagingplaysacriticalroleindiagnosis.Inthecurrentscenario,therearevariousradiological process being carried out towards medical image where Magnetic ResonanceImaging (MRI) is considered to offer appropriate localization of the tumor in the brain image.Anextensivereviewofliteratureassociatedwithvariousstandardapproacheshasbeenstudied towards addressing detection process of brain tumor. This approach has advantagesand also limitations in the implementation. However, the common fact observed in all theexisting approaches is that the brain MRI image is directly used in certain detection algorithmwithout considering the fact that there could be possibilities of certain artifacts within MRI.This also results in outliers when various analytical schemes are applied over brain MRIimage in order to perform detection. This is the prime research challenge that has not beenaddressedin existingsystemandhenceitisconsidered inproposedstudy. newline
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URI: http://hdl.handle.net/10603/598158
Appears in Departments:R V College of Engineering

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01_titlepage.pdfAttached File312.17 kBAdobe PDFView/Open
02_prelimpage.pdf878.48 kBAdobe PDFView/Open
03_content.pdf592.75 kBAdobe PDFView/Open
04_abstract.pdf478.26 kBAdobe PDFView/Open
05_chapter1.pdf698.97 kBAdobe PDFView/Open
06_chapter2.pdf522.7 kBAdobe PDFView/Open
07_chapter3.pdf4.84 MBAdobe PDFView/Open
08_chapter4.pdf1.98 MBAdobe PDFView/Open
09_chapter5.pdf2.95 MBAdobe PDFView/Open
10_chapter6.pdf402.28 kBAdobe PDFView/Open
11_annexures.pdf436.57 kBAdobe PDFView/Open
80_recommendation.pdf454.37 kBAdobe PDFView/Open
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