Colorectal Cancer Detection using Image Processing based on IGVF Model
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 2
Abstract
Colorectal cancer is the third most common cancer in both men and women. Computed Tomography (CT) Colonography is a valid technique for detecting and screening colorectal cancers. In order to accomplish an effective way to identify colon cancer at an early stage, digital images of colon polyps have been investigated. In this paper, an improved gradient vector flow (IGVF) is considered as an essential method to segment an image appropriately. This new algorithm, IGVF can improve GVF snake model’s ability to capture thin boundary indentation like the boundary of cancer images. The segmented candidates are typically characterized by features describing like the polyp shape and its internal intensity distribution. Such features will serve as input for the classification system. Classification is performed by Support Vector Machine (SVM).Finally, measure the overlap between the manual and the algorithm segmentation to test the accuracy of frame work. It is expected to obtain greater accuracy and to produce good segmentation results of colonic polyps.
Authors and Affiliations
G. Shantha Lakshmi, Prof. B. Mohamed FaizeBasha
Keywords
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- EP ID EP147369
- DOI 10.9790/0661-16233943
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