Segmentation of Lung Tumor in CT Images using Graph Cuts

K  Vidhya; S  Revathi; S  Sahaya Selva Ashwini  and S  Vanitha

doi:10.17485/ijst/2016/v9iS1/108428

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Segmentation of Lung Tumor in CT Images using Graph Cuts

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9iS1/108428

Year: 2016, Volume: 9, Issue: Special Issue 1, Pages: 1-3

Original Article

Segmentation of Lung Tumor in CT Images using Graph Cuts

K. Vidhya^1*, 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
Vidhya
Department of Electronics and Communication Engineering
Email:[email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

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