Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: Special Issue 1, Pages: 1-3
K. Vidhya1*, S. Revathi 2 , S. Sahaya Selva Ashwini2 and S. Vanitha2
1 Department of Electronics and Communication Engineering, Velammal Engineering College, Ambattur-Red Hills Road, Velammal Nagar, Chennai - 600066, Tamil Nadu,India; [email protected]
2 Department of Electronics and Communication Engineering, Vel Tech, #42 Avadi-Vel Tech Road, Avadi, Chennai, Tamil Nadu, India; [email protected]
*Author for correspondence
Department of Electronics and Communication Engineering
Background/Objectives: The goal of this method is to obtain optimal segmentation by minimizing the energy using max-flow. Methods/Statistical Analysis: Image segmentation is partitioning the image based on similarities. The noise and low contrast in Computed Tomography (CT) images makes the segmentation process difficult. Thus the physiological informationfromCTimage is integratedusing the graphcutmethodto gethighcontrast andgoodboundaries. Findings: The graph cut method provides the shape term and region term to locate the tumor site. Improvements/Applications: Graph cut approach solves binary problems.
Keywords: Computed Tomography, Energy Minimization, Graph Cut, Image Segmentation
Subscribe now for latest articles and news.