A Novel Approach for Solving Medical Image Segmentation Problems with ACM
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 11
Abstract
In this paper we proposed a novel segmentation algorithm for medical image segmentation that employs an active contour model (ACM) using level set method. This algorithm takes advantage of local edge feature algorithm for accurately drive the contour to required boundary region. The analysis and detection of any kind of brain tumors from magnetic resonance imaging (MRI) is very important for radiologists and image processing researchers. If objects of interest and their boundaries can be located correctly, meaningful visual information would be provided to the physicians, making the following analysis much easier. Within the numerous image segmentation algorithms, active contour model is widely used with its clear curve for the object. This algorithm measures the alignment between the evolving contour’s normal direction of movement and the image’s gradient in the adjacent region located inside and outside of the evolving contour and also considers the average edge intensity in the adjacent region located inside and outside of the evolving contour. This allows minimizing the negative effect of weak edges on the segmentation accuracy.
Authors and Affiliations
Chidadala. Janardhan, Dr. K. V. Ramanaiah, Dr. K. Babulu
Keywords
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- EP ID EP392937
- DOI 10.9790/9622-0711064047.
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