Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/519570
Title: Certain investigations on the performance analysis of lung tumor detection system
Researcher: Manoj Senthil K
Guide(s): Meeradevi T
Keywords: ANFIS
CANFIS
Engineering
Engineering and Technology
Engineering Electrical and Electronic
Lung Tumor
University: Anna University
Completed Date: 2023
Abstract: Even though, the machine learning algorithms for tumor region detection in lung CT images obtain optimum tumor detection accuracy, they require large number of external features for training the machine learning classification algorithm designed. Further, these algorithms are not suitable for the diagnosis of segmented tumor region due to the requirements of large number of lung CT images. To overcome such limitations in the conventional machine learning algorithms, the deep learning algorithm is proposed in this chapter for tumor region detection and diagnosis in lung CT images. The diagnosed abnormal images are further classified as Earlyand#8223; and Advancedand#8223; stages. Experiments carried out in this research work uses LIDC open access dataset. The proposed lung tumor detection and classification method also is analyzed with respect to deep learning algorithm, ANFIS and CANFIS classification approaches.
Pagination: xvii, 129 p.
URI: http://hdl.handle.net/10603/519570
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File25.43 kBAdobe PDFView/Open
02_prelim_pages.pdf3.5 MBAdobe PDFView/Open
03_content.pdf480.77 kBAdobe PDFView/Open
04_abstract.pdf128.21 kBAdobe PDFView/Open
05_chapter 1.pdf340.9 kBAdobe PDFView/Open
06_chapter 2.pdf173.08 kBAdobe PDFView/Open
07_chapter 3.pdf1.02 MBAdobe PDFView/Open
08_chapter 4.pdf666.96 kBAdobe PDFView/Open
09_chapter 5.pdf536.09 kBAdobe PDFView/Open
10_annexures.pdf140.97 kBAdobe PDFView/Open
80_recommendation.pdf82.5 kBAdobe PDFView/Open
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