research-article

Interactive differential evolution for prostate ultrasound image thresholding

Authors:

Arman Darvish,

Shahryar Rahnamayan,

Zaid S. MohamadAuthors Info & Claims

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

Pages 501 - 508

https://doi.org/10.1145/2330784.2330864

Published: 07 July 2012 Publication History

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Abstract

Image thresholding is a method of image segmentation which applies to grayscale images. Thresholding is a challenging task and many techniques have been introduced to offer a global technique that can be applied to all kind of images. In this paper an interactive method is introduced and its result is compared to a well known method (Otsu). The experimental verifications are conducted on prostate ultrasound images and also non-medical images.

References

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K.V. Price, R.M. Storn, J.A. Lampinen, Differential Evolution A Practical Approach to Global Optimization, Springer, 2005, ISBN:3540209506.

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S. Rahnamayan, H.R. Tizhoosh, M.M.A. Salama, Automatic Acquisition of Image Filtering and Object Extraction Procedures from Ground-Truth Samples, Journal of Advanced Computational Intelligence and Intelligent Informatics, Volume 13, No. 2, March 2009, pp. 115--127.

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[3]

S. Rahnamayan, H.R. Tizhoosh, Magdy M.A. Salama, Image Thresholding Using Differntial Evolution, Medical Instrument Analysis and Machine Intelligence Research Group Faculty of Engineering, University of Waterloo

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J. Graf and W. Banzhaf, "Interactive evolution of images" in 4th Annual Conf. on Evolutionary Programming (J. R. Mc-Donnell, R. G Reynolds, and D. B. Fogel, eds. ), (San Diego, CA, USA), pp. 53--56, MIT Press, Mar. 1995.

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Rahnamayan, S., H.R.Tizhoosh and M.M.A Salama. "Opposition-based Differential Evolution" IEEE Trans. Evolutionary Computation, 12: 64--79, 2008

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Rizvi SRahnamayan S(2018)Interactive Evolutionary Parameter Optimization for Eulerian Video Magnification2018 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI.2018.8628652(10-16)Online publication date: Nov-2018
https://doi.org/10.1109/SSCI.2018.8628652

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Interactive differential evolution for prostate ultrasound image thresholding
1. Theory of computation

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GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

July 2012

1586 pages

ISBN:9781450311786

DOI:10.1145/2330784

Editor:
Terence Soule
University of Idaho, USA
,
General Chair:
Jason H. Moore
Dartmouth College, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 07 July 2012

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SIGEVO

GECCO '12: Genetic and Evolutionary Computation Conference

July 7 - 11, 2012

Pennsylvania, Philadelphia, USA

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Rizvi SRahnamayan S(2018)Interactive Evolutionary Parameter Optimization for Eulerian Video Magnification2018 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI.2018.8628652(10-16)Online publication date: Nov-2018
https://doi.org/10.1109/SSCI.2018.8628652

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Abstract

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Prostate Segmentation in Ultrasound and Magnetic Resonance Images

Fisher–Tippett Region-Merging Approach to Transrectal Ultrasound Prostate Lesion Segmentation

Brain voxel classification in magnetic resonance images using niche differential evolution based Bayesian inference of variational mixture of Gaussians

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