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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:

Fuzzy based image edge detection algorithm for blood vessel detection in retinal images
Farid Orujov, Rytis Maskeliūnas, Robertas Damaševičius, et al.
Applied Soft Computing (2020) Vol. 94, pp. 106452-106452
Closed Access | Times Cited: 168

Showing 1-25 of 168 citing articles:

Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition
Sheeba Lal, Saeed Ur Rehman, Jamal Hussain Shah, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3922-3922
Open Access | Times Cited: 101
Detection of COVID-19 Patients from CT Scan and Chest X-ray Data Using Modified MobileNetV2 and LIME
Md Manjurul Ahsan, Redwan Nazim, Zahed Siddique, et al.
Healthcare (2021) Vol. 9, Iss. 9, pp. 1099-1099
Open Access | Times Cited: 75
An Efficient Approach for the Detection of Brain Tumor Using Fuzzy Logic and U-NET CNN Classification
Sarmad Maqsood, Robertas Damaševičius, Faisal Mehmood Shah
Lecture notes in computer science (2021), pp. 105-118
Closed Access | Times Cited: 67
An enhanced deep image model for glaucoma diagnosis using feature-based detection in retinal fundus
Law Kumar Singh, Pooja Sharma, Hitendra Garg, et al.
Medical & Biological Engineering & Computing (2021) Vol. 59, Iss. 2, pp. 333-353
Closed Access | Times Cited: 62
Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients
Sarmad Maqsood, Robertas Damaševičius, Rytis Maskeliūnas
Sensors (2021) Vol. 21, Iss. 11, pp. 3865-3865
Open Access | Times Cited: 62
Detection of diabetic retinopathy using a fusion of textural and ridgelet features of retinal images and sequential minimal optimization classifier
Lakshmana Kumar Ramasamy, Shynu Gopalan Padinjappurathu, Seifedine Kadry, et al.
PeerJ Computer Science (2021) Vol. 7, pp. e456-e456
Open Access | Times Cited: 61
Optimization of IoT-Based Artificial Intelligence Assisted Telemedicine Health Analysis System
Heng Yu, Zhiqing Zhou
IEEE Access (2021) Vol. 9, pp. 85034-85048
Open Access | Times Cited: 54
A retinal blood vessel segmentation based on improved D-MNet and pulse-coupled neural network
Xiangyu Deng, Jinhong Ye
Biomedical Signal Processing and Control (2021) Vol. 73, pp. 103467-103467
Closed Access | Times Cited: 48
Retinal blood vessel segmentation using pixel-based feature vector
Buket Toptaş, Davut Hanbay
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 103053-103053
Closed Access | Times Cited: 44
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
Retinal Vessel Segmentation, a Review of Classic and Deep Methods
Ali Khandouzi, Ali Ariafar, Zahra Mashayekhpour, et al.
Annals of Biomedical Engineering (2022) Vol. 50, Iss. 10, pp. 1292-1314
Closed Access | Times Cited: 36
Diabetic retinopathy prediction based on deep learning and deformable registration
Mohammed Oulhadj, Jamal Riffi, Chaimae Khodriss, et al.
Multimedia Tools and Applications (2022) Vol. 81, Iss. 20, pp. 28709-28727
Closed Access | Times Cited: 34
Retinal image blood vessel classification using hybrid deep learning in cataract diseased fundus images
Yogesh Kumar, Bharat Gupta
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104776-104776
Closed Access | Times Cited: 19
Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection
D. Dhinakaran, L. Srinivasan, D. Selvaraj, et al.
International Journal of Electronics and Communication Engineering (2023) Vol. 10, Iss. 8, pp. 9-21
Open Access | Times Cited: 18
Retinal vessel segmentation to diagnose diabetic retinopathy using fundus images: A survey
K. Radha, Yepuganti Karuna
International Journal of Imaging Systems and Technology (2023) Vol. 34, Iss. 1
Closed Access | Times Cited: 16
Leveraging Negative Capacitance CNTFETs for Image Processing: An Ultra-Efficient Ternary Image Edge Detection Hardware
Fereshteh Behbahani, Mohammad Khaleqi Qaleh Jooq, Mohammad Hossein Moaiyeri, et al.
IEEE Transactions on Circuits and Systems I Regular Papers (2021) Vol. 68, Iss. 12, pp. 5108-5119
Closed Access | Times Cited: 39
A Fuzzy Rule-Based System for Classification of Diabetes
Khalid Mahmood Aamir, Laiba Sarfraz, Muhammad Ramzan, et al.
Sensors (2021) Vol. 21, Iss. 23, pp. 8095-8095
Open Access | Times Cited: 33
Retinal Vessel Extraction via Assisted Multi-Channel Feature Map and U-Net
Surbhi Bhatia, Shadab Alam, Mohammed Shuaib, et al.
Frontiers in Public Health (2022) Vol. 10
Open Access | Times Cited: 26
Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector
Shahzaib Iqbal, Khuram Naveed, Syed S. Naqvi, et al.
Digital Signal Processing (2023) Vol. 139, pp. 104075-104075
Closed Access | Times Cited: 15
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
Automatic coronary artery segmentation of CCTA images using UNet with a local contextual transformer
Qianjin Wang, Lisheng Xu, Lu Wang, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 14
An effective vessel segmentation method using SLOA-HGC
Zerui Liu, Junliang Du, Weisi Dai, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
CMS-net: Edge-aware multimodal MRI feature fusion for brain tumor segmentation
Chunjie Lv, Biyuan Li, Xiuwei Wang, et al.
Image and Vision Computing (2025) Vol. 156, pp. 105481-105481
Closed Access
A precise image-based retinal blood vessel segmentation method using TAOD-CFNet
Yixin Yang, Lixiang Sun, Zhiwen Tang, et al.
Biomedical Signal Processing and Control (2025) Vol. 107, pp. 107815-107815
Closed Access
ECM-TransUNet: Edge-enhanced multi-scale attention and convolutional Mamba for medical image segmentation
Chunjie Lv, Biyuan Li, Xiuwei Wang, et al.
Biomedical Signal Processing and Control (2025) Vol. 107, pp. 107845-107845
Closed Access
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