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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:

Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review
Parvathy Jyothi, A. Robert Singh
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 2923-2969
Closed Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

Brain Tumor Detection and Classification Using Intelligence Techniques: An Overview
Shubhangi Solanki, Uday Pratap Singh, Siddharth Singh Chouhan, et al.
IEEE Access (2023) Vol. 11, pp. 12870-12886
Open Access | Times Cited: 96
A novel Swin transformer approach utilizing residual multi-layer perceptron for diagnosing brain tumors in MRI images
İshak Paçal
International Journal of Machine Learning and Cybernetics (2024) Vol. 15, Iss. 9, pp. 3579-3597
Open Access | Times Cited: 39
Brain tumour segmentation framework with deep nuanced reasoning and Swin‐T
Xu Yang, Kun Yu, Guanqiu Qi, et al.
IET Image Processing (2024) Vol. 18, Iss. 6, pp. 1550-1564
Open Access | Times Cited: 25
Enhancing EfficientNetv2 with global and efficient channel attention mechanisms for accurate MRI-Based brain tumor classification
İshak Paçal, Ömer Çelik, Bilal Bayram, et al.
Cluster Computing (2024) Vol. 27, Iss. 8, pp. 11187-11212
Open Access | Times Cited: 17
Modified U-Net with attention gate for enhanced automated brain tumor segmentation
Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana, et al.
Neural Computing and Applications (2025)
Closed Access | Times Cited: 1
Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images
K. Divya Lakshmi, Sibi Amaran, Subbulakshmi Ganesan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Feature Extraction Using a Residual Deep Convolutional Neural Network (ResNet-152) and Optimized Feature Dimension Reduction for MRI Brain Tumor Classification
Suganya Athisayamani, Robert Singh Antonyswamy, S. Velliangiri, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 668-668
Open Access | Times Cited: 36
A review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 9
Recent deep learning-based brain tumor segmentation models using multi-modality magnetic resonance imaging: a prospective survey
Zain Ul Abıdın, Rizwan Ali Naqvi, Amir Haider, et al.
Frontiers in Bioengineering and Biotechnology (2024) Vol. 12
Open Access | Times Cited: 9
Vision transformers in multi-modal brain tumor MRI segmentation: A review
Pengyu Wang, Qiushi Yang, Zhibin He, et al.
Meta-Radiology (2023) Vol. 1, Iss. 1, pp. 100004-100004
Open Access | Times Cited: 17
Brain Tumor Segmentation Using Ensemble CNN-Transfer Learning Models: DeepLabV3plus and ResNet50 Approach
Shoffan Saifullah, Rafał Dreżewski
Lecture notes in computer science (2024), pp. 340-354
Closed Access | Times Cited: 6
MVSI-Net: Multi-view attention and multi-scale feature interaction for brain tumor segmentation
Junding Sun, Ming Xi Hu, Xiaosheng Wu, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106484-106484
Open Access | Times Cited: 5
Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario
Aidan Boyd, Zezhong Ye, Sanjay P. Prabhu, et al.
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 4
Closed Access | Times Cited: 5
Automatic Brain Tumor Segmentation Using Convolutional Neural Networks: U-Net Framework with PSO-Tuned Hyperparameters
Shoffan Saifullah, Rafał Dreżewski
Lecture notes in computer science (2024), pp. 333-351
Closed Access | Times Cited: 5
MUNet: a novel framework for accurate brain tumor segmentation combining UNet and mamba networks
Lijuan Yang, Qiang Dong, Da Lin, et al.
Frontiers in Computational Neuroscience (2025) Vol. 19
Open Access
SPP_CNN: Spatial Pyramid Pooling for Optimizing Brain Tumor Classification
Suri babu Nuthalapati, A. R. Bushara, K M Abubeker
Lecture notes in electrical engineering (2025), pp. 1-16
Closed Access
Hydrogel-based nanoparticles: revolutionizing brain tumor treatment and paving the way for future innovations
Alireza Shadab, Simin Farokhi, Arshia Fakouri, et al.
European journal of medical research (2025) Vol. 30, Iss. 1
Open Access
Gabrain-Net: An Optimized Gabor-Integrated U-Net for Multimodal Brain Tumor MRI Segmentation
Ekram Chamseddine, Lotfi Tlig, lotfi Chaari, et al.
(2025)
Closed Access
XAI-MRI: an ensemble dual-modality approach for 3D brain tumor segmentation using magnetic resonance imaging
Ahmeed Suliman Farhan, Muhammad Khalid, Umar Manzoor
Frontiers in Artificial Intelligence (2025) Vol. 8
Open Access
Pseudo-deep unsupervised model-based clustering for brain tumor detection in magnetic resonance images
Rahman Farnoosh, Fatemeh Aghagoli
Applied Soft Computing (2025), pp. 112940-112940
Closed Access
A dual-stage framework for segmentation of the brain anatomical regions with high accuracy
Pegah Sharifian, Alireza Karimian, Hossein Arabi
Magnetic Resonance Materials in Physics Biology and Medicine (2025)
Closed Access
Cycle generative adversarial Transformer network for MRI brain tumor segmentation
Muqing Zhang, Qiule Sun, Yutong Han, et al.
Neural Computing and Applications (2025)
Closed Access
Brain tumor segmentation with deep learning: Current approaches and future perspectives
Akash Verma, Arun Kumar Yadav
Journal of Neuroscience Methods (2025), pp. 110424-110424
Closed Access
Brain tumor detection and segmentation: Interactive framework with a visual interface and feedback facility for dynamically improved accuracy and trust
Kashfia Sailunaz, Deniz Beştepe, Sleiman Alhajj, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284418-e0284418
Open Access | Times Cited: 15
HSA-net with a novel CAD pipeline boosts both clinical brain tumor MR image classification and segmentation
Zekuan Yu, Xiang Li, Jiaxin Li, et al.
Computers in Biology and Medicine (2024) Vol. 170, pp. 108039-108039
Closed Access | Times Cited: 4
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