English

hidden markov random fields and cuckoo search method for medical image segmentation

Image and Video Processing 2020-05-20 v1 Computer Vision and Pattern Recognition Machine Learning

Abstract

Segmentation of medical images is an essential part in the process of diagnostics. Physicians require an automatic, robust and valid results. Hidden Markov Random Fields (HMRF) provide powerful model. This latter models the segmentation problem as the minimization of an energy function. Cuckoo search (CS) algorithm is one of the recent nature-inspired meta-heuristic algorithms. It has shown its efficiency in many engineering optimization problems. In this paper, we use three cuckoo search algorithm to achieve medical image segmentation.

Keywords

Cite

@article{arxiv.2005.09377,
  title  = {hidden markov random fields and cuckoo search method for medical image segmentation},
  author = {EL-Hachemi Guerrout and Ramdane Mahiou and Dominique Michelucci and Boukabene Randa and Ouali Assia},
  journal= {arXiv preprint arXiv:2005.09377},
  year   = {2020}
}

Comments

5 pages, 2 figures, 8 tables

R2 v1 2026-06-23T15:39:25.725Z