Cogprints

Chromosome Segmentation and Investigations using Generalized Gradient Vector Flow Active Contours

Prabhu Britto, Albert and Ravindran, Gurubatham (2005) Chromosome Segmentation and Investigations using Generalized Gradient Vector Flow Active Contours. [Journal (On-line/Unpaginated)]

Full text available as:

[img]
Preview
 PDF
323Kb

Abstract

We investigated Generalized Gradient Vector Flow Active Contours as a suitable boundary mapping technique for Chromosome spread images which have variability in shape and size, expecting to yield a robust segmentation scheme that can be used for segmentation of similar class of images based on optimal set of parameter values. It is found experimentally that a unique set of parameter values is required for boundary mapping each chromosome image. Characterization studies have established that each parameter has an optimal range of values within which good boundary mapping results can be obtained in similar class of images. Statistical testing validates the experimental results.

Item Type:Journal (On-line/Unpaginated)
Keywords:Generalized Gradient Vector Flow, Active Contours, Deformable Curves, Chromosome, Boundary Mapping, Characterization
Subjects:JOURNALS > Online Journal of Health and Allied Sciences
ID Code:4552
Deposited By: Kakkilaya Bevinje, Dr. Srinivas
Deposited On:20 Oct 2005
Last Modified:11 Mar 2011 08:56

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

1. McInerney T, Terzopoulos D. Deformable models in medical image analysis. IEEE Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. 1996. p171-180.

2. Kass M, Witkin A, Terzopoulos D. Snakes: active contour models. Int. J. Comp. Vision. 1987;1:321-331.

3. Rueckert D. Segmentation and tracking in cardiovascular MR images using geometrically deformable models and templates. PhD thesis. Imperial College of Science, Technology and Medicine. London. 1997.

4. Xu C, Prince JL. Gradient Vector Flow: A New External Force for Snakes. IEEE Proc. Conf. on Comp. Vis. Patt. Recog. (CVPR'97). 1997. p66-71

5. Leroy B, Herlin I, Cohen LD. Multi-resolution algorithms for active contour models. In 12th Intl. Conf. on Analysis and Optimization of Systems.1996:58-65.

6. Cohen LD. On active contours and balloons. CVGIP: Image Understanding. 1991 March;53(2):211-218.

7. Cohen LD, Cohen I. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. On Pattern Anal. Machine Intell. 1993 Nov.;15(11):1131-1147.

8. Davatzikos C Prince JL. An active contour model for mapping the cortex. IEEE Trans. on Medical Imaging. 1995 March;14(1):65-80.

9. Davatzikos C, Prince JL. Convexity analysis of active contour models. In Proc. Conf. on Info. Sci. and Sys. 1994. p581-587.

10. Abrantes AJ, Marques JS. A class of constrained clustering algorithms for object boundary extraction. IEEE Trans. on Image Processing. 1996 Nov.;5(11):1507-1521.

11. Prince JL, Xu C. A new external force model for snakes. In 1996 Image and Multidimensional Signal Processing Workshop. 1996. p30-31.

12. Xu C, Prince JL. Gradient Vector Flow Deformable Models. In Handbook of Medical Imaging. Academic Press. Sept. 2000.

13. Xu C, Prince JL. Snakes, shapes and gradient vector flow. IEEE Trans. on Image Processing. 1998 March;7(3):359-369.

14. Xu C, Prince JL. Generalized gradient vector flow external forces for active contours. Signal Processing. 1998;71:131-139.

Metadata

Repository Staff Only: item control page

Cogprints is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.