Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 Effective Semi-Supervised Approach for Liver CT Image Segmentation
Kai Han, Lu Liu, Yuqing Song, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 8, pp. 3999-4007
Closed Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation
Rushi Jiao, Yichi Zhang, Le Ding, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107840-107840
Open Access | Times Cited: 120
PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN
Wei Wang, Yanrong Pei, SHUI-HUA WANG, et al.
Biocell (2022) Vol. 47, Iss. 2, pp. 373-384
Open Access | Times Cited: 91
Deep semi-supervised learning for medical image segmentation: A review
Kai Han, Victor S. Sheng, Yuqing Song, et al.
Expert Systems with Applications (2024) Vol. 245, pp. 123052-123052
Closed Access | Times Cited: 42
FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery
Xueyu Zhang, Qingxiang Li, Wei Li, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 3, pp. 1552-1563
Closed Access | Times Cited: 15
OPT-CO: Optimizing pre-trained transformer models for efficient COVID-19 classification with stochastic configuration networks
Ziquan Zhu, Lu Liu, Robert C. Free, et al.
Information Sciences (2024) Vol. 680, pp. 121141-121141
Open Access | Times Cited: 13
Own-background contrastive learning guided by pseudo-label for semi-supervised medical image segmentation
Huijie Fan, Jinghan Cao, Xi’ai Chen, et al.
Applied Soft Computing (2025), pp. 112749-112749
Closed Access
Multi-task Heterogeneous Framework for Semi-supervised Medical Image Segmentation
Jinghan Cao, Huijie Fan, Shengpeng Fu, et al.
Lecture notes in computer science (2025), pp. 77-88
Closed Access
Uncertainty-aware self-training with adversarial data augmentation for semi-supervised medical image segmentation
Juan Cao, Jiaran Chen, Jinjia Liu, et al.
Biomedical Signal Processing and Control (2025) Vol. 105, pp. 107561-107561
Closed Access
Correlation-based switching mean teacher for semi-supervised medical image segmentation
Guocheng DENG, Hao Sun, Wei Xie
Neurocomputing (2025), pp. 129818-129818
Closed Access
Better Pseudo-Labeling for Semi-Supervised Domain Generalization in Medical Magnetic Resonance Image Segmentation
Liangqing Hu, Zuqiang Meng, Chao-Hong Tan, et al.
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
SM2C – Boost the semi-supervised segmentation for medical image by using meta pseudo labels and mixed images
Yifei Wang, Chuhong Zhu
Biomedical Signal Processing and Control (2025) Vol. 107, pp. 107869-107869
Closed Access
Consistency and adversarial semi-supervised learning for medical image segmentation
Yongqiang Tang, Shilei Wang, Yuxun Qu, et al.
Computers in Biology and Medicine (2023) Vol. 161, pp. 107018-107018
Closed Access | Times Cited: 11
PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN.
Wei Wang, Yanrong Pei, Shuihua Wang‎, et al.
PubMed (2023) Vol. 47, Iss. 2, pp. 373-384
Closed Access | Times Cited: 7
Coarse-Refined Consistency Learning Using Pixel-Level Features for Semi-Supervised Medical Image Segmentation
Jie Du, Xiaoci Zhang, Peng Liu, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 8, pp. 3970-3981
Closed Access | Times Cited: 7
CotepRes-Net: An efficient U-Net based deep learning method of liver segmentation from Computed Tomography images
Jiahua Zhu, Ziteng Liu, Wenpeng Gao, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105660-105660
Closed Access | Times Cited: 7
DSST: A dual student model guided student–teacher framework for semi-supervised medical image segmentation
Boliang Li, Yan Wang, Yaming Xu, et al.
Biomedical Signal Processing and Control (2023) Vol. 90, pp. 105890-105890
Closed Access | Times Cited: 7
Semi-Supervised Disease Classification Based on Limited Medical Image Data
Yan Zhang, Chun Li, Zhaoxia Liu, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 3, pp. 1575-1586
Open Access | Times Cited: 2
Multi-task Learning to Improve Semantic Segmentation of CBCT Scans using Image Reconstruction
Maximilian Tschuchnig, Julia Coste‐Marin, Philipp Steininger, et al.
Informatik aktuell (2024), pp. 243-248
Closed Access | Times Cited: 2
Semi-supervised intracranial aneurysm segmentation via reliable weight selection
Cao Wei, Xin Chen, Jianping Lv, et al.
The Visual Computer (2024)
Closed Access | Times Cited: 2
Segment Anything Model for Semi-Supervised Medical Image Segmentation via Selecting Reliable Pseudo-Labels
Ning Li, Lianjin Xiong, Wei Qiu, et al.
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 6
Advanced Artificial Intelligence Methods for Medical Applications
Thitirat Siriborvornratanakul
Lecture notes in computer science (2023), pp. 329-340
Closed Access | Times Cited: 6
An Implicit-Explicit Prototypical Alignment Framework for Semi-Supervised Medical Image Segmentation
Chunna Tian, Zhenxi Zhang, Xinbo Gao, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 2, pp. 929-940
Closed Access | Times Cited: 5
Liver Segmentation with MT-UNet++
Sijing Yang, Peng Sun, Yongbo Liang, et al.
IFMBE proceedings (2024), pp. 205-216
Closed Access | Times Cited: 1
MBAHIL: Design of a Multimodal Hybrid Bioinspired Model for Augmentation of Hyperspectral Imagery via Iterative Learning for Continuous Efficiency Enhancements
Dipen Saini, Rahul Malik, Rachit Garg, et al.
IEEE Access (2023) Vol. 11, pp. 47781-47793
Open Access | Times Cited: 4
CA-UNet Segmentation Makes a Good Ischemic Stroke Risk Prediction
Yuqi Zhang, Mengbo Yu, Chao Tong, et al.
Interdisciplinary Sciences Computational Life Sciences (2023) Vol. 16, Iss. 1, pp. 58-72
Closed Access | Times Cited: 4
Page 1 - Next Page

Scroll to top