Cuckoo Search-Based Scale Value Optimization for Enhancement in Retinal Image Registration

2016 ◽  
pp. 453-460
Author(s):  
Ebenezer Daniel ◽  
J. Anitha
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Cuckoo Search

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

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 659 ◽  
Author(s):  
Sayan Chakraborty ◽  
Ratika Pradhan ◽  
Amira S. Ashour ◽  
Luminita Moraru ◽  
Nilanjan Dey
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Firefly Algorithm ◽  
Cuckoo Search ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Swarm Optimization ◽  
Registration Error ◽  
Registration Process ◽  
Fast Processing

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.

scholarly journals Grey Wolf Based Wang’s Demons for Retinal Image Registration

2020 ◽  
Author(s):  
Sayan Chakraborty ◽  
Ratika Pradhan ◽  
Amira S. Ashour ◽  
Luminita Moraru ◽  
Nilanjan Dey
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Firefly Algorithm ◽  
Cuckoo Search ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Swarm Optimization ◽  
Registration Error ◽  
Registration Process ◽  
Fast Processing

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.

Gaussian field estimator with manifold regularization for retinal image registration

2019 ◽  
Vol 157 ◽  
pp. 225-235 ◽  
Author(s):  
Jiahao Wang ◽  
Jun Chen ◽  
Huihui Xu ◽  
Shuaibin Zhang ◽  
Xiaoguang Mei ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Manifold Regularization ◽  
Gaussian Field

scholarly journals RETINAL IMAGE REGISTRATION AND COMPARISON FOR CLINICAL DECISION SUPPORTDi Xiao

2012 ◽  
Vol 05 (09) ◽  
Author(s):  
Di Xiao ◽  
Janardhan Vignarajan ◽  
Jane Lock ◽  
Shaun Frost ◽  
Mei-Ling Tay Kearney ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Clinical Decision

Non-rigid retinal image registration using an unsupervised structure-driven regression network

2020 ◽  
Vol 404 ◽  
pp. 14-25
Author(s):  
Beiji Zou ◽  
Zhiyou He ◽  
Rongchang Zhao ◽  
Chengzhang Zhu ◽  
Wangmin Liao ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image
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