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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Series: | International Journal of Biomedical Imaging |
Online Access: | http://dx.doi.org/10.1155/2008/759354 |
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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 |
work_keys_str_mv |
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_version_ |
1716794956743442432 |