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Feature-Based Retinal Image Registration Using D-Saddle Feature
المؤلفون المشاركون
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.
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-10-24
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1180804
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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