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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:

Retinal Vessel Segmentation Using Minimum Spanning Superpixel Tree Detector
Bin Sheng, Ping Li, Shuangjia Mo, et al.
IEEE Transactions on Cybernetics (2018) Vol. 49, Iss. 7, pp. 2707-2719
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Deep neural network correlation learning mechanism for CT brain tumor detection
Marcin Woźniak, Jakub Siłka, Michał Wieczorek
Neural Computing and Applications (2021) Vol. 35, Iss. 20, pp. 14611-14626
Open Access | Times Cited: 184
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: 166
Image Projection Network: 3D to 2D Image Segmentation in OCTA Images
Mingchao Li, Yerui Chen, Zexuan Ji, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 39, Iss. 11, pp. 3343-3354
Closed Access | Times Cited: 153
Dual Encoder-Based Dynamic-Channel Graph Convolutional Network With Edge Enhancement for Retinal Vessel Segmentation
Yang Li, Yue Zhang, Weigang Cui, et al.
IEEE Transactions on Medical Imaging (2022) Vol. 41, Iss. 8, pp. 1975-1989
Closed Access | Times Cited: 100
Multiview High Dynamic Range Image Synthesis Using Fuzzy Broad Learning System
Hongbin Guo, Bin Sheng, Ping Li, et al.
IEEE Transactions on Cybernetics (2019) Vol. 51, Iss. 5, pp. 2735-2747
Open Access | Times Cited: 91
An Efficient Blood-Cell Segmentation for the Detection of Hematological Disorders
Pradeep Kumar Das, Sukadev Meher, Rutuparna Panda, et al.
IEEE Transactions on Cybernetics (2021) Vol. 52, Iss. 10, pp. 10615-10626
Closed Access | Times Cited: 79
Global Transformer and Dual Local Attention Network via Deep-Shallow Hierarchical Feature Fusion for Retinal Vessel Segmentation
Yang Li, Yue Zhang, Jingyu Liu, et al.
IEEE Transactions on Cybernetics (2022) Vol. 53, Iss. 9, pp. 5826-5839
Closed Access | Times Cited: 63
Retinal Vessel Segmentation With Skeletal Prior and Contrastive Loss
Yubo Tan, Kai-Fu Yang, Shixuan Zhao, et al.
IEEE Transactions on Medical Imaging (2022) Vol. 41, Iss. 9, pp. 2238-2251
Closed Access | Times Cited: 58
Semi-supervised segmentation of echocardiography videos via noise-resilient spatiotemporal semantic calibration and fusion
Huisi Wu, Jiasheng Liu, Fangyan Xiao, et al.
Medical Image Analysis (2022) Vol. 78, pp. 102397-102397
Closed Access | Times Cited: 45
Res2Unet: A multi-scale channel attention network for retinal vessel segmentation
Xuejian Li, Jiaqi Ding, Jijun Tang, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 14, pp. 12001-12015
Closed Access | Times Cited: 39
A review of retinal vessel segmentation for fundus image analysis
Qing Qin, Yuanyuan Chen
Engineering Applications of Artificial Intelligence (2023) Vol. 128, pp. 107454-107454
Closed Access | Times Cited: 23
CoVi-Net: A hybrid convolutional and vision transformer neural network for retinal vessel segmentation
Minshan Jiang, Yongfei Zhu, Xuedian Zhang
Computers in Biology and Medicine (2024) Vol. 170, pp. 108047-108047
Closed Access | Times Cited: 9
A Comprehensive Review and New Taxonomy on Superpixel Segmentation
Isabela Borlido Barcelos, Felipe Belém, Leonardo João, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 8, pp. 1-39
Open Access | Times Cited: 8
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
Deep Retinal Image Segmentation With Regularization Under Geometric Priors
Venkateswararao Cherukuri, Vijay Kumar B.G., Raja Bala, et al.
IEEE Transactions on Image Processing (2019) Vol. 29, pp. 2552-2567
Open Access | Times Cited: 69
Efficient Body Motion Quantification and Similarity Evaluation Using 3-D Joints Skeleton Coordinates
Aouaidjia Kamel, Bin Sheng, Ping Li, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2019) Vol. 51, Iss. 5, pp. 2774-2788
Open Access | Times Cited: 60
Outdoor Shadow Estimating Using Multiclass Geometric Decomposition Based on BLS
Zhihua Chen, Ting Gao, Bin Sheng, et al.
IEEE Transactions on Cybernetics (2018) Vol. 50, Iss. 5, pp. 2152-2165
Closed Access | Times Cited: 48
Improving retinal vessel segmentation with joint local loss by matting
He Zhao, Huiqi Li, Li Cheng
Pattern Recognition (2019) Vol. 98, pp. 107068-107068
Closed Access | Times Cited: 46
Dual Multiscale Mean Teacher Network for Semi-Supervised Infection Segmentation in Chest CT Volume for COVID-19
Liansheng Wang, Jiacheng Wang, Lei Zhu, et al.
IEEE Transactions on Cybernetics (2022) Vol. 53, Iss. 10, pp. 6363-6375
Open Access | Times Cited: 25
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
Extraction of Blood Vessels in Fundus Images of Retina through Hybrid Segmentation Approach
Ramakrishnan Sundaram, K. S. Ravichandran, Premaladha Jayaraman, et al.
Mathematics (2019) Vol. 7, Iss. 2, pp. 169-169
Open Access | Times Cited: 42
IPN-V2 and OCTA-500: Methodology and Dataset for Retinal Image Segmentation.
Mingchao Li, Yuhan Zhang, Zexuan Ji, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 37
RADCU-Net: residual attention and dual-supervision cascaded U-Net for retinal blood vessel segmentation
Yong Yang, Weiguo Wan, Shuying Huang, et al.
International Journal of Machine Learning and Cybernetics (2022) Vol. 14, Iss. 5, pp. 1605-1620
Closed Access | Times Cited: 17
A lightweight network guided with differential matched filtering for retinal vessel segmentation
Yubo Tan, Shixuan Zhao, Kai-Fu Yang, et al.
Computers in Biology and Medicine (2023) Vol. 160, pp. 106924-106924
Closed Access | Times Cited: 9
A new deep learning approach for the retinal hard exudates detection based on superpixel multi-feature extraction and patch-based CNN
Chenxi Huang, Yongshuo Zong, Yimin Ding, et al.
Neurocomputing (2020) Vol. 452, pp. 521-533
Open Access | Times Cited: 27
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