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http://hdl.handle.net/10603/453030
Title: | Certain investigations on hybrid image Analysis techniques for diagnosis of Brain tumor |
Researcher: | Janardhana prabhu, S |
Guide(s): | Malathi, V |
Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic Medical imaging Brain tumor |
University: | Anna University |
Completed Date: | 2021 |
Abstract: | Image processing is a vast domain that processes the images to obtain newlineuseful information and it can be applied in various applications like remote newlinesensing, medical imaging, face detection, fiber defect detection, forgery newlinedetection etc. In image processing, four common processes are used and they are newlinepre-processing, feature extraction, segmentation and classification. The main newlineobjective of the present work is to find the best algorithms to handle different newlinekinds of inputs such as multi-sequence and multi resolution images. The newlineapproaches of each step are selected based on the type of input images. newlineFor pre-processing step, different kinds of pre-processing approaches newlineare needed for different imagings. To remove the salt and pepper and speckle newlinenoises, median filter could be a suitable choice. Thresholding process is another newlinekind for tracing the edges in the images. The selected pre-processing step in this newlinethesis is suitable for extracting the original form of brain MR images. newlineImage segmentation is the process of separating the images into newlinedifferent parts in order to evaluate a specific substance and its margins. Cancer newlinecan be defined as the uncontrolled, unnatural growth and division of the cells in newlinethe body. Occurrence, as a mass, of these unnatural cell growth and division in newlinethe brain tissue is called a brain tumor. Magnetic Resonance Imaging (MRI) is newlinethe most commonly used technique for diagnosing brain tumours. Exact newlineinformation about the affected area is critical for proper treatment. Since MRI newlinediagnosis generates a large amount of data, an automated segmentation newlinetechnique is necessary to obtain precise information of tumor. In the initial work newlineof this thesis, Depth-First Search (DFS) segmentation algorithm based graph newlinetheory has been presented. Based on their proximity in the image, image pixels newlineare arranged into a tree-like structure newline |
Pagination: | xiv,144p. |
URI: | http://hdl.handle.net/10603/453030 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 24.25 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.61 MB | Adobe PDF | View/Open | |
03_content.pdf | 148.72 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 9.35 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 403.78 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 350.51 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 936.41 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 885.06 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.35 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 154.24 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 68.51 kB | Adobe PDF | View/Open |
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