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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:

An Unsupervised Retinal Vessel Segmentation Using Hessian and Intensity Based Approach
Musaed Alhussein, Khursheed Aurangzeb, Syed Irtaza Haider
IEEE Access (2020) Vol. 8, pp. 165056-165070
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Contrast Enhancement of Fundus Images by Employing Modified PSO for Improving the Performance of Deep Learning Models
Khursheed Aurangzeb, Sheraz Aslam, Musaed Alhussein, et al.
IEEE Access (2021) Vol. 9, pp. 47930-47945
Open Access | Times Cited: 61
A novel framework for retinal vessel segmentation using optimal improved frangi filter and adaptive weighted spatial FCM
Sakambhari Mahapatra, Sanjay Agrawal, Pranaba K. Mishro, et al.
Computers in Biology and Medicine (2022) Vol. 147, pp. 105770-105770
Closed Access | Times Cited: 36
Detecting retinal vasculature as a key biomarker for deep Learning-based intelligent screening and analysis of diabetic and hypertensive retinopathy
Muhammad Arsalan, Adnan Haider, Young Won Lee, et al.
Expert Systems with Applications (2022) Vol. 200, pp. 117009-117009
Closed Access | Times Cited: 31
A comprehensive survey on segmentation techniques for retinal vessel segmentation
Jair Cervantes, Jared Cervantes, Farid García‐Lamont, et al.
Neurocomputing (2023) Vol. 556, pp. 126626-126626
Closed Access | Times Cited: 15
FS-Net: Full scale network and adaptive threshold for improving extraction of micro-retinal vessel structures
Melaku N. Getahun, Oleg Y. Rogov, Dmitry V. Dylov, et al.
Pattern Recognition Letters (2025)
Closed Access
A multi-scale convolutional neural network with context for joint segmentation of optic disc and cup
Xin Yuan, Lingxiao Zhou, Shuyang Yu, et al.
Artificial Intelligence in Medicine (2021) Vol. 113, pp. 102035-102035
Closed Access | Times Cited: 27
An Efficient and Light Weight Deep Learning Model for Accurate Retinal Vessels Segmentation
Khursheed Aurangzeb, Rasha Sarhan Alharthi, Syed Irtaza Haider, et al.
IEEE Access (2022) Vol. 11, pp. 23107-23118
Open Access | Times Cited: 20
Systematic Development of AI-Enabled Diagnostic Systems for Glaucoma and Diabetic Retinopathy
Khursheed Aurangzeb, Rasha Sarhan Alharthi, Syed Irtaza Haider, et al.
IEEE Access (2023) Vol. 11, pp. 105069-105081
Open Access | Times Cited: 12
MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation
Jun Li, Ting Zhang, Yi Zhao, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 16
Machine Learning and AI Approaches for Analyzing Diabetic and Hypertensive Retinopathy in Ocular Images: A Literature Review
Miguel Urina‐Triana, Marlon Alberto Piñeres-Melo, Mirary Mantilla-Morrón, et al.
IEEE Access (2024) Vol. 12, pp. 54590-54607
Open Access | Times Cited: 3
A comprehensive review of artificial intelligence models for screening major retinal diseases
Bilal Hassan, Hina Raja, Taimur Hassan, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 3
An accurate unsupervised extraction of retinal vasculature using curvelet transform and classical morphological operators
Feudjio Ghislain, Saha Tchinda Beaudelaire, Tchiotsop Daniel
Computers in Biology and Medicine (2024) Vol. 178, pp. 108801-108801
Closed Access | Times Cited: 3
Feature preserving mesh network for semantic segmentation of retinal vasculature to support ophthalmic disease analysis
Syed Muhammad Ali Imran, Muhammad Waqas Saleem, Muhammad Talha Hameed, et al.
Frontiers in Medicine (2023) Vol. 9
Open Access | Times Cited: 8
A Review on Retinal Blood Vessel Enhancement and Segmentation Techniques for Color Fundus Photography
Sakambhari Mahapatra, Sanjay Agrawal, Pranaba K. Mishro, et al.
Critical Reviews in Biomedical Engineering (2023) Vol. 52, Iss. 1, pp. 41-69
Closed Access | Times Cited: 7
Diabetic retinopathy detection using supervised and unsupervised deep learning: a review study
Huma Naz, Neelu Jyothi Ahuja, Rahul Nijhawan
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 2
Deep neural network-based detection and segmentation of intracranial aneurysms on 3D rotational DSA
Xinke Liu, Junqiang Feng, Zhenhua Wu, et al.
Interventional Neuroradiology (2021) Vol. 27, Iss. 5, pp. 648-657
Open Access | Times Cited: 17
Segmenting Retinal Vessels Using a Shallow Segmentation Network to Aid Ophthalmic Analysis
Muhammad Arsalan, Adnan Haider, Ja Hyung Koo, et al.
Mathematics (2022) Vol. 10, Iss. 9, pp. 1536-1536
Open Access | Times Cited: 9
A Detailed Systematic Review on Retinal Image Segmentation Methods
Nihar Ranjan Panda, Ajit Kumar Sahoo
Journal of Digital Imaging (2022) Vol. 35, Iss. 5, pp. 1250-1270
Open Access | Times Cited: 9
A New Enhancement Edge Detection of Finger-Vein Identification for Carputer System
Chih‐Hsien Hsia, Zi-Han Yang, Hong-Jyun Wang, et al.
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 10127-10127
Open Access | Times Cited: 8
A Generalized Grayscale Image Processing Framework for Retinal Fundus Images
Siddhesh Yerramneni, Kotta Sai Vara Nitya, Sirikrishna Nalluri, et al.
(2023)
Closed Access | Times Cited: 4
Gabor-net with multi-scale hierarchical fusion of features for fundus retinal blood vessel segmentation
Tao Fang, Zhefei Cai, Yingle Fan
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 2, pp. 402-413
Closed Access | Times Cited: 1
Performance analysis of diabetic retinopathy using diverse image enhancement techniques
Dimple Nagpal, Surya Narayan Panda
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2022) Vol. 11, Iss. 2, pp. 185-196
Closed Access | Times Cited: 7
RETRACTED: Design and development of SER-UNet model for glaucoma image analysis
C Gobinath, M. P. Gopinath
Journal of Electronic Imaging (2022) Vol. 31, Iss. 04
Closed Access | Times Cited: 6
HDC-Net: A hierarchical dilation convolutional network for retinal vessel segmentation
Xiaolong Hu, Liejun Wang, Shuli Cheng, et al.
PLoS ONE (2021) Vol. 16, Iss. 9, pp. e0257013-e0257013
Open Access | Times Cited: 6
A Hybrid Fusion Method Combining Spatial Image Filtering with Parallel Channel Network for Retinal Vessel Segmentation
Cem Yakut, İlkay Öksüz, Sezer Ulukaya
Arabian Journal for Science and Engineering (2022) Vol. 48, Iss. 5, pp. 6149-6162
Closed Access | Times Cited: 4
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