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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:

A New Hybrid Algorithm for Retinal Vessels Segmentation on Fundus Images
Dhimas Arief Dharmawan, Di Li, Eng‐Poh Ng, et al.
IEEE Access (2019) Vol. 7, pp. 41885-41896
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Retinal Vessel Segmentation Using Deep Learning: A Review
Chunhui Chen, Joon Huang Chuah, Ali Raza, et al.
IEEE Access (2021) Vol. 9, pp. 111985-112004
Open Access | Times Cited: 110
Pemanfaatan Machine Learning dalam Berbagai Bidang: Review paper
Ahmad Roihan, Po Abas Sunarya, Ageng Setiani Rafika
IJCIT (Indonesian Journal on Computer and Information Technology) (2020) Vol. 5, Iss. 1
Open Access | Times Cited: 107
Comparative Analysis of Vessel Segmentation Techniques in Retinal Images
Azhar Imran, Jianqiang Li, Yan Pei, et al.
IEEE Access (2019) Vol. 7, pp. 114862-114887
Open Access | Times Cited: 99
Encoder Enhanced Atrous (EEA) Unet architecture for Retinal Blood vessel segmentation
V. Sathananthavathi, G. Indumathi
Cognitive Systems Research (2021) Vol. 67, pp. 84-95
Closed Access | Times Cited: 92
Automatic Retinal Blood Vessel Segmentation Based on Fully Convolutional Neural Networks
Yun Jiang, Hai Zhang, Ning Tan, et al.
Symmetry (2019) Vol. 11, Iss. 9, pp. 1112-1112
Open Access | Times Cited: 81
Recent trends and advances in fundus image analysis: A review
Shahzaib Iqbal, Tariq M. Khan, Khuram Naveed, et al.
Computers in Biology and Medicine (2022) Vol. 151, pp. 106277-106277
Closed Access | Times Cited: 57
A Comprehensive Review of Deep Learning Strategies in Retinal Disease Diagnosis Using Fundus Images
G Balla, Mohammad Farukh Hashmi, Zong Woo Geem, et al.
IEEE Access (2022) Vol. 10, pp. 57796-57823
Open Access | Times Cited: 55
Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images
Yanhong Liu, Ji Shen, Lei Yang, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106341-106341
Closed Access | Times Cited: 53
GDF-Net: A multi-task symmetrical network for retinal vessel segmentation
Jianyong Li, Ge Gao, Lei Yang, et al.
Biomedical Signal Processing and Control (2022) Vol. 81, pp. 104426-104426
Closed Access | Times Cited: 44
MAGF-Net: A multiscale attention-guided fusion network for retinal vessel segmentation
Jianyong Li, Ge Gao, Yanhong Liu, et al.
Measurement (2022) Vol. 206, pp. 112316-112316
Closed Access | Times Cited: 38
A hybrid evolutionary weighted ensemble of deep transfer learning models for retinal vessel segmentation and diabetic retinopathy detection
Richa Vij, Sakshi Arora
Computers & Electrical Engineering (2024) Vol. 115, pp. 109107-109107
Closed Access | Times Cited: 14
RETRACTED ARTICLE: Robust retinal blood vessel segmentation using convolutional neural network and support vector machine
Kishore Balasubramanian, N. P. Ananthamoorthy
Journal of Ambient Intelligence and Humanized Computing (2019) Vol. 12, Iss. 3, pp. 3559-3569
Closed Access | Times Cited: 54
Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issues, and knowledge gaps in fundus medical images
Aws A. Abdulsahib, Moamin A. Mahmoud, Mazin Abed Mohammed, et al.
Network Modeling Analysis in Health Informatics and Bioinformatics (2021) Vol. 10, Iss. 1
Closed Access | Times Cited: 52
Learning-based algorithms for vessel tracking: A review
Dengqiang Jia, Xiahai Zhuang
Computerized Medical Imaging and Graphics (2021) Vol. 89, pp. 101840-101840
Open Access | Times Cited: 51
Blood vessel segmentation in retinal fundus images for proliferative diabetic retinopathy screening using deep learning
P. Saranya, S. Prabakaran, Rahul Kumar, et al.
The Visual Computer (2021) Vol. 38, Iss. 3, pp. 977-992
Closed Access | Times Cited: 46
A Survey of Deep Learning for Retinal Blood Vessel Segmentation Methods: Taxonomy, Trends, Challenges and Future Directions
Olubunmi Omobola Sule
IEEE Access (2022) Vol. 10, pp. 38202-38236
Open Access | Times Cited: 33
A Systematic Review on Diabetic Retinopathy Detection Using Deep Learning Techniques
Richa Vij, Sakshi Arora
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 3, pp. 2211-2256
Closed Access | Times Cited: 32
Artificial Intelligence in Ophthalmology: A Meta-Analysis of Deep Learning Models for Retinal Vessels Segmentation
Md. Mohaimenul Islam, Tahmina Nasrin Poly, Bruno Walther, et al.
Journal of Clinical Medicine (2020) Vol. 9, Iss. 4, pp. 1018-1018
Open Access | Times Cited: 48
Micro-Vessel Image Segmentation Based on the AD-UNet Model
Zhongming Luo, Yu Zhang, Lei Zhou, et al.
IEEE Access (2019) Vol. 7, pp. 143402-143411
Open Access | Times Cited: 47
Retinal Blood Vessels and Optic Disc Segmentation Using U-Net
S. Alex David, C. Mahesh, V. Dhilip Kumar, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 23
An improved supervised and attention mechanism-based U-Net algorithm for retinal vessel segmentation
Zhendi Ma, Xiaobo Li
Computers in Biology and Medicine (2023) Vol. 168, pp. 107770-107770
Closed Access | Times Cited: 13
MSCNN-AM: A Multi-Scale Convolutional Neural Network With Attention Mechanisms for Retinal Vessel Segmentation
Qilong Fu, Shuqiu Li, Xin Wang
IEEE Access (2020) Vol. 8, pp. 163926-163936
Open Access | Times Cited: 32
Retinal vasculature extraction algorithm based on an improved and lightweight U-Net deep learning model using the dense block
Beaudelaire Saha Tchinda, Zidane Rigasse Tchoupou Segning, Daniel Tchiotsop, et al.
Multimedia Tools and Applications (2025)
Closed Access
Sclera-Net: Accurate Sclera Segmentation in Various Sensor Images Based on Residual Encoder and Decoder Network
Rizwan Ali Naqvi, Woong-Kee Loh
IEEE Access (2019) Vol. 7, pp. 98208-98227
Open Access | Times Cited: 30
Channel and Spatial Attention Aware UNet Architecture for Segmentation of Blood Vessels, Exudates and Microaneurysms in Diabetic Retinopathy
Meenakshi Sundaram
International journal of intelligent engineering and systems (2024) Vol. 17, Iss. 2, pp. 1-16
Open Access | Times Cited: 3
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