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Segmentation of Lung Tumor in CT Images using Graph Cuts
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 information from CT image is integrated using the graph cut method to get high contrast and good boundaries. 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.
Computed Tomography, Energy Minimization, Graph Cut, Image Segmentation
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