Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images

We propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed based upon their parametric and nonparametric arguments. The pixel intensities, gradient magnitude,...

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Main Authors: B. Dhalila S. Y. Khoodoruth, Harry C. S. Rughooputh, Wilfrid Lefer
Format: Article
Language:English
Published: Hindawi Limited 2008-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/2008/759354
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spelling doaj-7b98bc2762574b7e8d259c3fa3c15a272020-11-24T20:54:18ZengHindawi LimitedInternational Journal of Biomedical Imaging1687-41881687-41962008-01-01200810.1155/2008/759354759354Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan ImagesB. Dhalila S. Y. Khoodoruth0Harry C. S. Rughooputh1Wilfrid Lefer2Department of Computer Science, University of Pau and Pays de l'Adour, 64012 PauCedex, FranceDepartment of Electrical & Electronic Engineering, University of Mauritius, Reduit, MauritiusDepartment of Computer Science, University of Pau and Pays de l'Adour, 64012 PauCedex, FranceWe propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed based upon their parametric and nonparametric arguments. The pixel intensities, gradient magnitude, affinity map, and catchment basins of these methods are validated based upon various constraints evaluations. In this article, we also develop a new methodology for a computational pipeline that uses bilateral filtering, diffusion properties, watershed, and filtering with mathematical morphology operators for the contour extraction of the lesion in the feature available based mainly on the gradient function. The evaluations of the classification of these lesions are very briefly outlined in this context and are being undertaken by pattern recognition in another paper work.http://dx.doi.org/10.1155/2008/759354
collection DOAJ
language English
format Article
sources DOAJ
author B. Dhalila S. Y. Khoodoruth
Harry C. S. Rughooputh
Wilfrid Lefer
spellingShingle B. Dhalila S. Y. Khoodoruth
Harry C. S. Rughooputh
Wilfrid Lefer
Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
International Journal of Biomedical Imaging
author_facet B. Dhalila S. Y. Khoodoruth
Harry C. S. Rughooputh
Wilfrid Lefer
author_sort B. Dhalila S. Y. Khoodoruth
title Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
title_short Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
title_full Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
title_fullStr Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
title_full_unstemmed Semi-Automatic Integrated Segmentation Approaches and Contour Extraction Applied to Computed Tomography Scan Images
title_sort semi-automatic integrated segmentation approaches and contour extraction applied to computed tomography scan images
publisher Hindawi Limited
series International Journal of Biomedical Imaging
issn 1687-4188
1687-4196
publishDate 2008-01-01
description We propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed based upon their parametric and nonparametric arguments. The pixel intensities, gradient magnitude, affinity map, and catchment basins of these methods are validated based upon various constraints evaluations. In this article, we also develop a new methodology for a computational pipeline that uses bilateral filtering, diffusion properties, watershed, and filtering with mathematical morphology operators for the contour extraction of the lesion in the feature available based mainly on the gradient function. The evaluations of the classification of these lesions are very briefly outlined in this context and are being undertaken by pattern recognition in another paper work.
url http://dx.doi.org/10.1155/2008/759354
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