6533b853fe1ef96bd12ac2eb

RESEARCH PRODUCT

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

El-hachemi GuerroutRamdane MahiouDominique MichelucciBoukabene RandaOuali Assia

subject

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesComputer Science - Machine LearningComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)FOS: Electrical engineering electronic engineering information engineeringComputer Science - Computer Vision and Pattern RecognitionElectrical Engineering and Systems Science - Image and Video Processing[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)

description

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.

yearjournalcountryeditionlanguage
2020-12-11
http://arxiv.org/abs/2005.09377