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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:

Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Kaveri A. Thakoor, Xinhui Li, Emmanouil Tsamis, et al.
(2019)
Closed Access | Times Cited: 60

Showing 26-50 of 60 citing articles:

The OCT RNFL Probability Map and Artifacts Resembling Glaucomatous Damage
Sol La Bruna, Anvit Rai, Grace Mao, et al.
Translational Vision Science & Technology (2022) Vol. 11, Iss. 3, pp. 18-18
Open Access | Times Cited: 12
Glaucoma Detection From Raw Circumpapillary OCT Images Using Fully Convolutional Neural Networks
Gabriel García, Rocío del Amor, Adrián Colomer, et al.
2022 IEEE International Conference on Image Processing (ICIP) (2020), pp. 2526-2530
Closed Access | Times Cited: 17
A Semantically Flexible Feature Fusion Network for Retinal Vessel Segmentation
Tariq M. Khan, Antonio Robles‐Kelly, Syed S. Naqvi
Communications in computer and information science (2020), pp. 159-167
Closed Access | Times Cited: 17
An Evaluation of a New 24-2 Metric for Detecting Early Central Glaucomatous Damage
Donald C. Hood, Abinaya Thenappan, Emmanouil Tsamis, et al.
American Journal of Ophthalmology (2020) Vol. 223, pp. 119-128
Open Access | Times Cited: 16
Strategies to Improve Convolutional Neural Network Generalizability and Reference Standards for Glaucoma Detection From OCT Scans
Kaveri A. Thakoor, Xinhui Li, Emmanouil Tsamis, et al.
Translational Vision Science & Technology (2021) Vol. 10, Iss. 4, pp. 16-16
Open Access | Times Cited: 14
RC-Net: A Convolutional Neural Network for Retinal Vessel Segmentation
Tariq M. Khan, Antonio Robles‐Kelly, Syed S. Naqvi
(2021), pp. 01-07
Open Access | Times Cited: 13
Global optical coherence tomography measures for detecting the progression of glaucoma have fundamental flaws
Ashley Sun, Emmanouil Tsamis, Melvi Eguia, et al.
Eye (2021) Vol. 35, Iss. 11, pp. 2973-2982
Open Access | Times Cited: 12
Retinal Vessel Segmentation Based on the Anam-Net Model
Khursheed Aurangzeb, Syed Irtaza Haider, Musaed Alhussein
Elektronika ir Elektrotechnika (2022) Vol. 28, Iss. 3, pp. 54-64
Open Access | Times Cited: 8
Possibilities of Explainable Artificial Intelligence for Glaucoma Detection Using the LIME Method as an Example
Egor N. Volkov, Aleksej N. Averkin
(2023), pp. 130-133
Closed Access | Times Cited: 4
BranchFusionNet: An energy-efficient lightweight framework for superior retinal vessel segmentation
Jing Qin, Zhiguang Qin, Peng Xiao
Peer-to-Peer Networking and Applications (2024) Vol. 17, Iss. 5, pp. 3133-3145
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
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
A study to identify limitations of existing automated systems to detect glaucoma at initial and curable stage
Tehmina Khalil, Muhammad Usman Akram, Samina Khalid, et al.
International Journal of Imaging Systems and Technology (2021) Vol. 31, Iss. 3, pp. 1155-1173
Closed Access | Times Cited: 10
RETRACTED ARTICLE: Glaucoma detection and classification using modified level set segmentation and pattern classification neural network
N S Jeya Shyla, W. R. Sam Emmanuel
Multimedia Tools and Applications (2022) Vol. 82, Iss. 10, pp. 15797-15815
Closed Access | Times Cited: 7
Visualization Techniques to Enhance the Explainability and Usability of Deep Learning Models in Glaucoma
Xiulan Zhang, Fei Li, Biao Wang, et al.
Asia-Pacific Journal of Ophthalmology (2023) Vol. 12, Iss. 4, pp. 347-348
Open Access | Times Cited: 3
Applied Explainable Artificial Intelligence (XAI) in the classification of retinal images for support in the diagnosis of Glaucoma
Cleverson Vieira, Marcus Vinícius De Castro Oliveira, Marcelo de Paiva Guimarães, et al.
(2023)
Closed Access | Times Cited: 2
Detection of Glaucoma using Convolutional Neural Network (CNN) with Super Resolution Generative Adversarial Network (SRGAN)
P.S. Nandhini, P. Srinath, P. Veeramanikandan
2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) (2022), pp. 1034-1040
Closed Access | Times Cited: 3
An improved ensemble deep learning framework for glaucoma detection
K. J. Subha, R. Rajavel, B. Paulchamy
Multimedia Tools and Applications (2024)
Closed Access
Automated Glaucoma Detection and Assessment using CNN from Fundus Images
B. Mahesh, S Sathiya Priya, Ashok Kumar T
(2024), pp. 01-06
Closed Access
Automated Identification of Clinically Relevant Regions in Glaucoma OCT Reports Using Expert Eye Tracking Data and Deep Learning
Ye Tian, Anurag Sharma, S Mehta, et al.
Translational Vision Science & Technology (2024) Vol. 13, Iss. 10, pp. 24-24
Open Access
Interpretable multimodal classification for age-related macular degeneration diagnosis
Carla Vairetti, Sebastián Maldonado, Loreto Cuitiño, et al.
PLoS ONE (2024) Vol. 19, Iss. 11, pp. e0311811-e0311811
Open Access
Did the OCT Show Progression Since the Last Visit?
Donald C. Hood, Bruna Melchior, Emmanouil Tsamis, et al.
Journal of Glaucoma (2020) Vol. 30, Iss. 4, pp. e134-e145
Open Access | Times Cited: 3
Can Glaucoma Suspect Data Help to Improve the Performance of Glaucoma Diagnosis?
Ashkan Abbasi, Bhavna Antony, Sowjanya Gowrisankaran, et al.
Translational Vision Science & Technology (2023) Vol. 12, Iss. 8, pp. 6-6
Open Access | Times Cited: 1
Phase Difference Network for Efficient Differentiation of Hepatic Tumors with Multi-Phase CT
Yuanfeng Wu, Geng Chen, Feng Zhan, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023), pp. 1-5
Closed Access | Times Cited: 1
Predicting Glaucoma Severity Levels in Human Eyes: Integrating CNN and Random Forest for accurate classification
Ankita Suryavanshi, Vinay Kukreja, Ayush Dogra, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 1

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