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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine Learning and Deep Learning Techniques for Optic Disc and Cup Segmentation – A Review
Mohammed Alawad, Abdulrhman Aljouie, Suhailah Alamri, et al.
Clinical ophthalmology (2022) Vol. Volume 16, pp. 747-764
Open Access | Times Cited: 24

Showing 24 citing articles:

Multiscale guided attention network for optic disc segmentation of retinal images
AZM Ehtesham Chowdhury, Andrew Mehnert, Graham J. Mann, et al.
Computer Methods and Programs in Biomedicine Update (2025), pp. 100180-100180
Open Access | Times Cited: 1
C2FTFNet: Coarse-to-fine transformer network for joint optic disc and cup segmentation
Yugen Yi, Yan Jiang, Bin Zhou, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 107215-107215
Closed Access | Times Cited: 21
The AI Revolution in Glaucoma: Bridging Challenges with Opportunities
Fei Li, Biao Wang, Zefeng Yang, et al.
Progress in Retinal and Eye Research (2024) Vol. 103, pp. 101291-101291
Closed Access | Times Cited: 6
Highly accurate and precise automated cup-to-disc ratio quantification for glaucoma screening
Abadh K. Chaurasia, Connor J. Greatbatch, Xikun Han, et al.
Ophthalmology Science (2024) Vol. 4, Iss. 5, pp. 100540-100540
Open Access | Times Cited: 4
A comprehensive review of optic disc segmentation methods in adult and pediatric retinal images: from conventional methods to artificial intelligence (CR-ODSeg-AP-CM2AI)
Avinash Bansal, Jan Kubíček, Marek Penhaker, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access
Artificial Intelligence in Ophthalmology: Advantages and Limits
Hariton Costin, Monica Fira, Liviu Goraș
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 1913-1913
Open Access
mlscorecheck: Testing the consistency of reported performance scores and experiments in machine learning
György Kovács, Attila Fazekas
Neurocomputing (2024) Vol. 583, pp. 127556-127556
Open Access | Times Cited: 2
LC-MANet: Location-constrained joint optic disc and cup segmentation via multiplex aggregation network
Jiaming Yu, Nan Chen, Jun Li, et al.
Computers & Electrical Engineering (2024) Vol. 118, pp. 109423-109423
Closed Access | Times Cited: 2
Multi-Scale Attention U-Net for Optic Disc and Optic Cup Segmentation in Retinal Fundus Images
Chanmean Meas, Wei Guo, Md Helal Miah
(2024)
Closed Access | Times Cited: 2
Performance Evaluation of Different Object Detection Models for the Segmentation of Optical Cups and Discs
Gendry Alfonso-Francia, Jesús Carlos Pedraza‐Ortega, Mariana Badillo-Fernández, et al.
Diagnostics (2022) Vol. 12, Iss. 12, pp. 3031-3031
Open Access | Times Cited: 10
Testing the consistency of performance scores reported for binary classification problems
Attila Fazekas, György Kovács
Applied Soft Computing (2024) Vol. 164, pp. 111993-111993
Open Access | Times Cited: 1
Explainable Artificial Intelligence in Deep Learning Neural Nets-Based Digital Images Analysis
Alexey N. Averkin, Egor N. Volkov, Sergey Yarushev
Journal of Computer and Systems Sciences International (2024) Vol. 63, Iss. 1, pp. 175-203
Closed Access | Times Cited: 1
Explainable artificial intelligence in deep learning neural nets-based digital images analysis
Alexey N. Averkin, Egor N. Volkov, Sergey Yarushev
Известия Российской академии наук Теория и системы управления (2024), Iss. 1, pp. 150-178
Closed Access | Times Cited: 1
Quantization of Optic Disc Characteristics in Young Adults Based on Artificial Intelligence
Xiaoxiao Guo, Runkuan Li, Xiuzhen Lu, et al.
Current Eye Research (2023) Vol. 48, Iss. 11, pp. 1068-1077
Open Access | Times Cited: 3
Artificial intelligence for glaucoma: state of the art and future perspectives
Rafael Correia Barão, Ruben Hemelings, Luis M. G. Abegão, et al.
Current Opinion in Ophthalmology (2023) Vol. 35, Iss. 2, pp. 104-110
Closed Access | Times Cited: 2
Segmentação de Imagens de Fundo de Olho e Identificação de Padrão ISNT para Auxílio ao Diagnóstico de Glaucoma
M. Gomes, Rafael Stubs Parpinelli
(2024), pp. 1-8
Open Access
A study on Retinopathy of Prematurity(ROP) Screening Using Deep Learning Approaches and a Blood Vessel Segmentation Framework for ROP Affected Eyes
Kalyanasundaram Madhu, Shinu Mathew John, Asha Joseph, et al.
(2024), pp. 1-10
Closed Access
Highly accurate and precise automated cup-to-disc ratio quantification for glaucoma screening
Abadh K. Chaurasia, Connor J. Greatbatch, Xikun Han, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
MA‐ResUNet: Multi‐attention optic cup and optic disc segmentation based on improved U‐Net
Xiaoqian Zhang, Ying Lin, Linxuan Li, et al.
IET Image Processing (2024) Vol. 18, Iss. 12, pp. 3128-3142
Open Access
A Comprehensive Approach for an Interpretable Diabetic Macular Edema Grading System Based on ConvUNext
Zaira García-Nonoal, Atoany Fierro-Radilla, Mariko Nakano-Miyatake
Applied Sciences (2024) Vol. 14, Iss. 16, pp. 7262-7262
Open Access
Assessing coarse-to-fine deep learning models for optic disc and cup segmentation in fundus images
Eugenia Moris, Nicolas Dazeo, Maria Paula Albina de Rueda, et al.
(2023), pp. 36-36
Open Access | Times Cited: 1
CDRNet: accurate cup-to-disc ratio measurement with tight bounding box supervision in fundus photography using deep learning
Juan Wang, Bin Xia
Multimedia Tools and Applications (2022) Vol. 82, Iss. 11, pp. 16455-16477
Open Access | Times Cited: 1
Mobile Implementation of Retinal Image Analysis for Efficient Vessel, Optic Disc, and Lesion Detection
Mubdiul Hossain, Aziah Ali, Noramiza Hashim, et al.
JOIV International Journal on Informatics Visualization (2023) Vol. 7, Iss. 3-2, pp. 1022-1022
Open Access
Improving Diabetes Management with Support Vector Machine based Fundus Image Analysis
P. Raghu Vamsi, Pawan Kumar Upadhyay
2022 8th International Conference on Signal Processing and Communication (ICSC) (2023), pp. 568-574
Closed Access
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