Feature-Based Retinal Image Registration Using D-Saddle Feature
Joint Authors
Abdul Wahab, Ainuddin Wahid
Kadri, Nahrizul Adib
Idris, Mohd Yamani Idna
Karim, Noor Khairiah A.
Ramli, Roziana
Hasikin, Khairunnisa
Ahmedy, Ismail
Ahmedy, Fatimah
Arof, H.
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-24
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma.
However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes.
A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels.
Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle) to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes.
D-Saddle is tested on Fundus Image Registration (FIRE) Dataset that consists of 134 retinal image pairs.
Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%), Harris-PIIFD (4%), H-M (16%), and Saddle (16%).
Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman) with the intensity uniformity metric among all methods.
Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.
American Psychological Association (APA)
Ramli, Roziana& Idris, Mohd Yamani Idna& Hasikin, Khairunnisa& Karim, Noor Khairiah A.& Abdul Wahab, Ainuddin Wahid& Ahmedy, Ismail…[et al.]. 2017. Feature-Based Retinal Image Registration Using D-Saddle Feature. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1180804
Modern Language Association (MLA)
Ramli, Roziana…[et al.]. Feature-Based Retinal Image Registration Using D-Saddle Feature. Journal of Healthcare Engineering No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1180804
American Medical Association (AMA)
Ramli, Roziana& Idris, Mohd Yamani Idna& Hasikin, Khairunnisa& Karim, Noor Khairiah A.& Abdul Wahab, Ainuddin Wahid& Ahmedy, Ismail…[et al.]. Feature-Based Retinal Image Registration Using D-Saddle Feature. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1180804
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180804