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Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques

In this paper we are going to discuss and analyze the different methods which are developed to detect the Lung nodules which cause the lung cancer. At the end of analyzing different methods, the new methodology of detecting the lung nodules using Spline Wavelet technique has been proposed in this pa...

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Autores principales: Senthil Kumar, T. K., Ganesh, E. N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Master Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3644416/
https://www.ncbi.nlm.nih.gov/pubmed/23675284
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author Senthil Kumar, T. K.
Ganesh, E. N.
author_facet Senthil Kumar, T. K.
Ganesh, E. N.
author_sort Senthil Kumar, T. K.
collection PubMed
description In this paper we are going to discuss and analyze the different methods which are developed to detect the Lung nodules which cause the lung cancer. At the end of analyzing different methods, the new methodology of detecting the lung nodules using Spline Wavelet technique has been proposed in this paper. Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels. The multi resolution property of Splines makes them prime candidates for constructing wavelet bases. Wavelet tool also let us to compress the original CT image to greater factor without any sacrifice in accuracy of nodule detection. Different Algorithms for segmentation/ detection of lung nodules from CT image is discussed in this paper.
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spelling pubmed-36444162013-05-07 Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques Senthil Kumar, T. K. Ganesh, E. N. Int J Biomed Sci Review Article In this paper we are going to discuss and analyze the different methods which are developed to detect the Lung nodules which cause the lung cancer. At the end of analyzing different methods, the new methodology of detecting the lung nodules using Spline Wavelet technique has been proposed in this paper. Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels. The multi resolution property of Splines makes them prime candidates for constructing wavelet bases. Wavelet tool also let us to compress the original CT image to greater factor without any sacrifice in accuracy of nodule detection. Different Algorithms for segmentation/ detection of lung nodules from CT image is discussed in this paper. Master Publishing Group 2013-03 /pmc/articles/PMC3644416/ /pubmed/23675284 Text en © T. K. Senthil Kumar et al. Licensee Master Publishing Group http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Review Article
Senthil Kumar, T. K.
Ganesh, E. N.
Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title_full Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title_fullStr Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title_full_unstemmed Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title_short Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques
title_sort proposed technique for accurate detection/segmentation of lung nodules using spline wavelet techniques
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3644416/
https://www.ncbi.nlm.nih.gov/pubmed/23675284
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