Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Grey Wolf Based Wang’s Demons for Retinal Image Registration

Version 1 : Received: 9 May 2020 / Approved: 10 May 2020 / Online: 10 May 2020 (16:11:54 CEST)

How to cite: Chakraborty, S.; Pradhan, R.; Ashour, A.S.; Moraru, L.; Dey, N. Grey Wolf Based Wang’s Demons for Retinal Image Registration. Preprints 2020, 2020050173 (doi: 10.20944/preprints202005.0173.v1). Chakraborty, S.; Pradhan, R.; Ashour, A.S.; Moraru, L.; Dey, N. Grey Wolf Based Wang’s Demons for Retinal Image Registration. Preprints 2020, 2020050173 (doi: 10.20944/preprints202005.0173.v1).

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.

Subject Areas

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

Comments (1)

Comment 1
Received: 12 May 2020
Commenter: yang li
The commenter has declared there is no conflict of interests.
Comment: very good
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