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Fully Leveraging Deep Learning Methods for Constructing Retinal Fundus Photomontages

التفاصيل البيبلوغرافية
العنوان: Fully Leveraging Deep Learning Methods for Constructing Retinal Fundus Photomontages
المؤلفون: Jooyoung Kim, Sojung Go, Kyoung Jin Noh, Sang Jun Park, Soochahn Lee
المصدر: Applied Sciences, Vol 11, Iss 4, p 1754 (2021)
بيانات النشر: MDPI AG, 2021.
سنة النشر: 2021
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: fundus photo, montage, object detection, keypoint matching, vessel segmentation, rigid registration, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Retinal photomontages, which are constructed by aligning and integrating multiple fundus images, are useful in diagnosing retinal diseases affecting peripheral retina. We present a novel framework for constructing retinal photomontages that fully leverage recent deep learning methods. Deep learning based object detection is used to define the order of image registration and blending. Deep learning based vessel segmentation is used to enhance image texture to improve registration performance within a two step image registration framework comprising rigid and non-rigid registration. Experimental evaluation demonstrates the robustness of our montage construction method with an increased amount of successfully integrated images as well as reduction of image artifacts.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/11/4/1754; https://doaj.org/toc/2076-3417
DOI: 10.3390/app11041754
URL الوصول: https://doaj.org/article/0b3cfdc73bcb4d179336fad496b94386
رقم الأكسشن: edsdoj.0b3cfdc73bcb4d179336fad496b94386
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app11041754