3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images
المؤلفون المشاركون
Rabbani, Hossein
Mehri Dehnavi, Alireza
Esmaeili, M.
المصدر
Journal of Electrical and Computer Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-01-31
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Spectral-Domain Optical Coherence Tomography (SD-OCT) is a widely used interferometric diagnostic technique in ophthalmology that provides novel in vivo information of depth-resolved inner and outer retinal structures.
This imaging modality can assist clinicians in monitoring the progression of Age-related Macular Degeneration (AMD) by providing high-resolution visualization of drusen.
Quantitative tools for assessing drusen volume that are indicative of AMD progression may lead to appropriate metrics for selecting treatment protocols.
To address this need, a fully automated algorithm was developed to segment drusen area and volume from SD-OCT images.
The proposed algorithm consists of three parts: (1) preprocessing, which includes creating binary mask and removing possible highly reflective posterior hyaloid that is used in accurate detection of inner segment/outer segment (IS/OS) junction layer and Bruch’s membrane (BM) retinal layers; (2) coarse segmentation, in which 3D curvelet transform and graph theory are employed to get the possible candidate drusenoid regions; (3) fine segmentation, in which morphological operators are used to remove falsely extracted elongated structures and get the refined segmentation results.
The proposed method was evaluated in 20 publically available volumetric scans acquired by using Bioptigen spectral-domain ophthalmic imaging system.
The average true positive and false positive volume fractions (TPVF and FPVF) for the segmentation of drusenoid regions were found to be 89.15% ± 3.76 and 0.17% ± .18%, respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Esmaeili, M.& Mehri Dehnavi, Alireza& Rabbani, Hossein. 2017. 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1175278
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Esmaeili, M.…[et al.]. 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1175278
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Esmaeili, M.& Mehri Dehnavi, Alireza& Rabbani, Hossein. 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1175278
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1175278
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر