Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/458517
Title: | Certain investigations on computer Aided colon cancer detection in Wireless capsule endoscopy images |
Researcher: | Shanmuga sundaram P |
Guide(s): | Santhiyakumari.N |
Keywords: | Engineering and Technology Computer Science Computer Science Information Systems Wireless Capsule Endoscopy Support Vector Mac |
University: | Anna University |
Completed Date: | 2021 |
Abstract: | The colon cancer is formed by uncontrollable growth of abnormal newlinecells in large intestine or colon that can affect both men and women, and it is newlinethird cancer disease in the world. At present, Wireless Capsule Endoscopy newline(WCE) screening method is utilized to identify colon cancer tumor at early newlinestage to save the patient life who affected by the colon cancer. In this WCE newlinemethod, the radiologist needs to analyze the colon polyps in a digital image newlineusing the computer-aided approach with accurate automatic tumor newlineclassification to detect the cancer tumor at an early stage. This kind of newlinecomputer aided approach can operate as an intermediate between input digital newlineimage and radiologist. The physicians felt difficult to identify the accurate newlineregion and it creates a challenge in detection of tumor cells. At present, in newlinecancer detection process computer-aided automatic medical image processing newlineplays a vital role. Therefore, the following computer aided approaches are newlinepresented to find the colon polyp or colon tumor in WCE images. newlineand#61623; Enhanced Computer-Aided Approach for Colon Cancer Detection in newlineWCE Images Using RoI Based Color Histogram and SVM2 newlineand#61623; Automatic Colon Cancer Detection in WCE Images Using ANFIS newlineClassifier With GLCM newlineIn the first method, the digital WCE image can be preprocessed newlineusing filtering and ROI based color histogram depending on the salient region newlinein the colon. In common, the salient region can be distinctive because of low newlineredundancy. Hence, the saliency is estimated by ROI based color histogram newlineon the basis of color and structure contrast in given colon image for the newlinefurther process of clustering and tumor classification in WCE image. The Kmeans newlineclustering can be employed to cluster the preprocessed digital image to newlinediscover the tumor of the colon newline |
Pagination: | xii,113p. |
URI: | http://hdl.handle.net/10603/458517 |
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 | 27.79 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 3.65 MB | Adobe PDF | View/Open | |
03_content.pdf | 288.78 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 162.25 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 2.77 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 2.3 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 982.56 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.11 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.33 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 834.19 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 416.88 kB | Adobe PDF | View/Open |
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