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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 Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI
Subhashis Banerjee, Sushmita Mitra, Francesco Masulli, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

A Deep Learning Model Based on Concatenation Approach for the Diagnosis of Brain Tumor
Neelum Noreen, Sellappan Palaniappan, Abdul Qayyum, et al.
IEEE Access (2020) Vol. 8, pp. 55135-55144
Open Access | Times Cited: 348
Brain tumor detection and classification using machine learning: a comprehensive survey
Javeria Amin, Muhammad Sharif, Anandakumar Haldorai, et al.
Complex & Intelligent Systems (2021) Vol. 8, Iss. 4, pp. 3161-3183
Open Access | Times Cited: 262
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
TimeDistributed-CNN-LSTM: A Hybrid Approach Combining CNN and LSTM to Classify Brain Tumor on 3D MRI Scans Performing Ablation Study
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, et al.
IEEE Access (2022) Vol. 10, pp. 60039-60059
Open Access | Times Cited: 94
Automated glioma grading on conventional MRI images using deep convolutional neural networks
Ying Zhuge, Holly Ning, Peter Mathen, et al.
Medical Physics (2020) Vol. 47, Iss. 7, pp. 3044-3053
Open Access | Times Cited: 130
Visual interpretability in 3D brain tumor segmentation network
Hira Saleem, Ahmad Raza Shahid, Basit Raza
Computers in Biology and Medicine (2021) Vol. 133, pp. 104410-104410
Closed Access | Times Cited: 61
A Review of Radiomics and Deep Predictive Modeling in Glioma Characterization
Sonal Gore, Tanay Chougule, Jayant Jagtap, et al.
Academic Radiology (2020) Vol. 28, Iss. 11, pp. 1599-1621
Closed Access | Times Cited: 62
Deep Neural Network-Based Novel Mathematical Model for 3D Brain Tumor Segmentation
Ajay S. Ladkat, Sunil L. Bangare, Vishal Jagota, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-8
Open Access | Times Cited: 36
Observing deep radiomics for the classification of glioma grades
Kazuma Kobayashi, Mototaka Miyake, Masamichi Takahashi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 38
A comparative study for glioma classification using deep convolutional neural networks
Hakan Özcan, Bülent Gürsel Emiroğlu, Hakan Sabuncuoğlu, et al.
Mathematical Biosciences & Engineering (2021) Vol. 18, Iss. 2, pp. 1550-1572
Open Access | Times Cited: 36
Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features
Zhenyuan Ning, Jiaxiu Luo, Qing Xiao, et al.
Annals of Translational Medicine (2021) Vol. 9, Iss. 4, pp. 298-298
Open Access | Times Cited: 35
A Convolutional Neural Network Combined With Prototype Learning Framework for Brain Functional Network Classification of Autism Spectrum Disorder
Yin Liang, Baolin Liu, Hesheng Zhang
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 2193-2202
Open Access | Times Cited: 32
Glioma Grade Classification using CNNs and Segmentation with an Adaptive Approach using Histogram Features in Brain MRIs
Çağin Özkaya, Şeref Sağıroğlu
IEEE Access (2023), pp. 1-1
Open Access | Times Cited: 15
Improving a neural network model by explanation-guided training for glioma classification based on MRI data
František Šefčík, Wanda Benešová
International Journal of Information Technology (2023) Vol. 15, Iss. 5, pp. 2593-2601
Open Access | Times Cited: 12
Deep learning LI-RADS grading system based on contrast enhanced multiphase MRI for differentiation between LR-3 and LR-4/LR-5 liver tumors
Yunan Wu, Gregory White, Tyler Cornelius, et al.
Annals of Translational Medicine (2020) Vol. 8, Iss. 11, pp. 701-701
Open Access | Times Cited: 38
Synergizing medical imaging and radiotherapy with deep learning
Hongming Shan, Xun Jia, Pingkun Yan, et al.
Machine Learning Science and Technology (2020) Vol. 1, Iss. 2, pp. 021001-021001
Open Access | Times Cited: 34
Brain Tumor Detection Based on Features Extracted and Classified Using a Low-Complexity Neural Network
Vasileios E. Papageorgiou
Traitement du signal (2021) Vol. 38, Iss. 3, pp. 547-554
Open Access | Times Cited: 27
Exploring Radiologic Criteria for Glioma Grade Classification on the BraTS Dataset
Paul Dequidt, Pascal Bourdon, Benoît Tremblais, et al.
IRBM (2021) Vol. 42, Iss. 6, pp. 407-414
Open Access | Times Cited: 26
WU-Net++: A novel enhanced Weighted U-Net++ model for brain tumor detection and segmentation from multi-parametric magnetic resonance scans
Suchismita Das, Rajni Dubey, Biswajit Jena, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 28, pp. 71885-71908
Closed Access | Times Cited: 2
MR Brain Tumour Classification Using a Deep Ensemble Learning Technique
B Anilkumar, Navdeep Kumar, K. Sowmya
(2023), pp. 1-6
Closed Access | Times Cited: 6
Survival and grade of the glioma prediction using transfer learning
S. Rubio, María Teresa Garcí­a-Ordás, Óscar García-Olalla Olivera, et al.
PeerJ Computer Science (2023) Vol. 9, pp. e1723-e1723
Open Access | Times Cited: 3
Recent advances in Glioma grade classification using machine and deep learning on MR data
Paul Dequidt, Pascal Bourdon, Olfa Ben Ahmed, et al.
(2019) Vol. 2, pp. 1-4
Closed Access | Times Cited: 6
Detection of Brain Tumor using CNN
Tapesh Kumar, Puneet Kumar Yadav, Vrinda Yadav
2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA) (2022) Vol. 80.2, pp. 1121-1126
Closed Access | Times Cited: 4
Radiogenomic analysis: 1p/19q codeletion based subtyping of low-grade glioma by analysing advanced biomedical texture descriptors
Sonal Gore, Jayant Jagtap
Journal of King Saud University - Computer and Information Sciences (2021) Vol. 34, Iss. 10, pp. 8449-8458
Open Access | Times Cited: 5
Optimizing Feature Representation via A Nested Network for Object Segmentation
Abdalrahman Alblwi, Kenneth E. Barner
2018 4th International Conference on Optimization and Applications (ICOA) (2022)
Closed Access | Times Cited: 3
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