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Grey-Wolf-Based Wang’s Demons for Retinal Image Registration

1
Department of Computer Applications, SMIT, Sikkim Manipal University, Sikkim 737136, India
2
Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta 31527, Egypt
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Department of Chemistry, Physics & Environment, Faculty of Sciences and Environment, Dunarea de Jos University of Galati, 47 Domneasca Str., 800008 Galati, Romania
4
Department of Information Technology, Techno International New Town, West Bengal 700156, India
*
Authors to whom correspondence should be addressed.
Entropy 2020, 22(6), 659; https://doi.org/10.3390/e22060659
Received: 7 May 2020 / Revised: 4 June 2020 / Accepted: 6 June 2020 / Published: 15 June 2020
(This article belongs to the Special Issue Entropy Based Image Registration)
Image registration has an imperative role in medical imaging. In this work, a grey-wolf optimizer (GWO)-based non-rigid demons registration is proposed to support the retinal image registration process. A comparative study of the proposed GWO-based demons registration framework with cuckoo search, firefly algorithm, and particle swarm optimization-based demons registration is conducted. In addition, a comparative analysis of different demons registration methods, such as Wang’s demons, Tang’s demons, and Thirion’s demons which are optimized using the proposed GWO is carried out. The results established the superiority of the GWO-based framework which achieved 0.9977 correlation, and fast processing compared to the use of the other optimization algorithms. Moreover, GWO-based Wang’s demons performed better accuracy compared to the Tang’s demons and Thirion’s demons framework. It also achieved the best less registration error of 8.36 × 10−5. View Full-Text
Keywords: demons registration; firefly algorithm; cuckoo search; grey-wolf optimization; correlation; image registration demons registration; firefly algorithm; cuckoo search; grey-wolf optimization; correlation; image registration
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MDPI and ACS Style

Chakraborty, S.; Pradhan, R.; S. Ashour, A.; Moraru, L.; Dey, N. Grey-Wolf-Based Wang’s Demons for Retinal Image Registration. Entropy 2020, 22, 659.

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