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Lung Nodules Detection, Segmentation and Classification using Ray Casting

Author(s):

Praveen H.Pawar , MARATHA MANDAL'S ENGINEERING COLLEGE BELAGAVI; Prof.Dhanashree P. Kutre, MARATHA MANDAL'S ENGINEERING COLLEGE BELAGAVI

Keywords:

CAD (Computer Aided Detection), CT (Computed Tomography)

Abstract

The proposed work is to present a novel approach for lung nodule segmentation in chest CT images using Level Sets. The shape model is fused with the image intensity statistical information in a variation segmentation framework. The nodule shape model is mapped to the image domain by a global transformation that includes inhomogeneous scales, rotation, and translation parameters. Transformation parameters evolve through gradient descent optimization to handle the shape alignment process and hence mark the boundaries of the nodule “head.” The embedding process takes into consideration the image intensity as well as prior shape information. A nonparametric density estimation approach is employed to handle the statistical intensity representation of the nodule and background regions. The proposed technique does not depend on nodule type or location.

Other Details

Paper ID: IJSRDV3I40907
Published in: Volume : 3, Issue : 4
Publication Date: 01/07/2015
Page(s): 1685-1688

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