Semi-automatic integrated segmentation approaches and contour extraction applied to computed tomography scan images

Authors:
B. Dhalila S. Y. Khoodoruth;Harry C. S. Rughooputh;Wilfrid Lefer
Affiliations:
Department of Computer Science, University of Pau and Pays de l'Adour, Pau Cedex, France;Department of Electrical & Electronic Engineering, University of Mauritius, Reduit, Mauritius;Department of Computer Science, University of Pau and Pays de l'Adour, Pau Cedex, France
Venue:
Journal of Biomedical Imaging
Year:
2008

Citing 11
Cited 0

Fast computation of morphological operations with arbitrary structuring elements

Pattern Recognition Letters
The watershed transform: definitions, algorithms and parallelization strategies

Fundamenta Informaticae - Special issue on mathematical morphology
Level set methods: an overview and some recent results

Journal of Computational Physics
Fast Surface Reconstruction Using the Level Set Method

VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Bilateral Filtering for Gray and Color Images

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Topological Segmentation in Three-Dimensional Vector Fields

IEEE Transactions on Visualization and Computer Graphics
Time-Varying Contour Topology

IEEE Transactions on Visualization and Computer Graphics
Thin Structure Segmentation and Visualization in Three-Dimensional Biomedical Images: A Shape-Based Approach

IEEE Transactions on Visualization and Computer Graphics
Shape analysis and fuzzy control for 3d competitive segmentation of brain structures with level sets

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Visualization for validation and improvement of three-dimensional segmentation algorithms

EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
3D soft segmentation and visualization of medical data based on nonlinear diffusion and distance functions

EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.