Firefly algorithm approach for rational bézier border reconstruction of skin lesions from macroscopic medical images

Authors: Galvez, A., Iglesias, A., Ugail, H., You, L., Haron, H. and Habib, Z.

Journal: 2019 13th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2019

ISBN: 9781728127415

DOI: 10.1109/SKIMA47702.2019.8982465

Abstract:

Image segmentation is a fundamental step for image processing of medical images. One of the most important tasks in this step is border reconstruction, which consists of constructing a border curve separating the organ or tissue of interest from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitting procedures from a collection of data points assumed to lie on the boundary of the object under analysis. However, standard mathematical optimization techniques do not provide satisfactory solutions to this problem. Some recent papers have applied evolutionary computation techniques to tackle this issue. Such works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational Bézier curves by applying the firefly algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on medical images of melanomas show that this method performs well and can be successfully applied to this problem.

http://eprints.bournemouth.ac.uk/34670/

Source: Scopus

Firefly Algorithm Approach For Rational Bezier Border Reconstruction of Skin Lesions from Macroscopic Medical Images

Authors: Galvez, A., Iglesias, A., Ugail, H., You, L., Haron, H., Habib, Z. and IEEE

Journal: 2019 13TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT AND APPLICATIONS (SKIMA)

ISSN: 2373-082X

http://eprints.bournemouth.ac.uk/34670/

Source: Web of Science (Lite)

Firefly algorithm approach for rational bézier border reconstruction of skin lesions from macroscopic medical images

Authors: Galvez, A., Iglesias, A., Ugail, H., You, L., Haron, H. and Habib, Z.

Conference: 13th International Conference on Software, Knowledge, Information Management and Applications

Dates: 26-28 August 2019

Journal: 2019 13th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2019

ISBN: 9781728127415

DOI: 10.1109/SKIMA47702.2019.8982465

Abstract:

© 2019 IEEE. Image segmentation is a fundamental step for image processing of medical images. One of the most important tasks in this step is border reconstruction, which consists of constructing a border curve separating the organ or tissue of interest from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitting procedures from a collection of data points assumed to lie on the boundary of the object under analysis. However, standard mathematical optimization techniques do not provide satisfactory solutions to this problem. Some recent papers have applied evolutionary computation techniques to tackle this issue. Such works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational Bézier curves by applying the firefly algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on medical images of melanomas show that this method performs well and can be successfully applied to this problem.

http://eprints.bournemouth.ac.uk/34670/

Source: Manual

Preferred by: Lihua You

Firefly algorithm approach for rational bézier border reconstruction of skin lesions from macroscopic medical images

Authors: Galvez, A., Iglesias, A., Ugail, H., You, L., Haron, H. and Habib, Z.

Conference: 13th International Conference on Software, Knowledge, Information Management and Applications

ISBN: 9781728127415

Abstract:

Image segmentation is a fundamental step for image processing of medical images. One of the most important tasks in this step is border reconstruction, which consists of constructing a border curve separating the organ or tissue of interest from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitting procedures from a collection of data points assumed to lie on the boundary of the object under analysis. However, standard mathematical optimization techniques do not provide satisfactory solutions to this problem. Some recent papers have applied evolutionary computation techniques to tackle this issue. Such works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational Bézier curves by applying the firefly algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on medical images of melanomas show that this method performs well and can be successfully applied to this problem.

http://eprints.bournemouth.ac.uk/34670/

Source: BURO EPrints