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

Sayan Chakraborty; Ratika Pradhan; Amira S Ashour; Luminita Moraru; Nilanjan Dey

doi:10.3390/e22060659

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

Entropy (Basel). 2020 Jun 15;22(6):659. doi: 10.3390/e22060659.

Authors

Sayan Chakraborty¹, Ratika Pradhan¹, Amira S Ashour², Luminita Moraru³, Nilanjan Dey⁴

Affiliations

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.
³ 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.

Abstract

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.

Keywords: correlation; cuckoo search; demons registration; firefly algorithm; grey-wolf optimization; image registration.