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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:

Brain Tumor Detection and Classification from Multi-sequence MRI: Study Using ConvNets
Subhashis Banerjee, Sushmita Mitra, Francesco Masulli, et al.
Lecture notes in computer science (2019), pp. 170-179
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

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 Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges
Muhammad Waqas Nadeem, Mohammed A. Al Ghamdi, Muzammil Hussain, et al.
Brain Sciences (2020) Vol. 10, Iss. 2, pp. 118-118
Open Access | Times Cited: 198
Deep Learning for Screening COVID-19 using Chest X-Ray Images
Sanhita Basu, Sushmita Mitra, Nilanjan Saha
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2020), pp. 2521-2527
Open Access | Times Cited: 165
Role of Ensemble Deep Learning for Brain Tumor Classification in Multiple Magnetic Resonance Imaging Sequence Data
Gopal S. Tandel, Ashish Tiwari, O. G. Kakde, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 481-481
Open Access | Times Cited: 45
RanMerFormer: Randomized vision transformer with token merging for brain tumor classification
Jian Wang, Siyuan Lu, Shuihua Wang‎, et al.
Neurocomputing (2024) Vol. 573, pp. 127216-127216
Open Access | Times Cited: 25
A Comprehensive Survey on Brain Tumor Diagnosis Using Deep Learning and Emerging Hybrid Techniques with Multi-modal MR Image
Saqib Ali, Jianqiang Li, Yan Pei, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 4871-4896
Closed Access | Times Cited: 59
A Transfer Learning–Based Active Learning Framework for Brain Tumor Classification
Ruqian Hao, Khashayar Namdar, Lin Liu, et al.
Frontiers in Artificial Intelligence (2021) Vol. 4
Open Access | Times Cited: 58
RETRACTED ARTICLE: Brain tumor magnetic resonance image classification: a deep learning approach
Machiraju Jaya Lakshmi, S. Nagaraja Rao
Soft Computing (2022) Vol. 26, Iss. 13, pp. 6245-6253
Closed Access | Times Cited: 39
Smart brain tumor diagnosis system utilizing deep convolutional neural networks
Yıldıray Anagün
Multimedia Tools and Applications (2023) Vol. 82, Iss. 28, pp. 44527-44553
Open Access | Times Cited: 32
Automatic brain tumor detection using CNN transfer learning approach
Vinayak K. Bairagi, Pratima Purushottam Gumaste, Seema Rajput, et al.
Medical & Biological Engineering & Computing (2023) Vol. 61, Iss. 7, pp. 1821-1836
Closed Access | Times Cited: 21
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 Learning-Based HCNN and CRF-RRNN Model for Brain Tumor Segmentation
Wu Deng, Qinke Shi, Miye Wang, et al.
IEEE Access (2020) Vol. 8, pp. 26665-26675
Open Access | Times Cited: 49
A systematic review on deep learning implementation in brain tumor segmentation, classification and prediction
Muhammad Adeel Abid, Kashif Munir
Multimedia Tools and Applications (2025)
Closed Access
CNN-LSTM Based Hybrid Approach for Precise Brain Tumour Classification
Sitanath Biswas, Santanu Sahoo, Saswati Rakshit, et al.
Learning and analytics in intelligent systems (2025), pp. 31-40
Closed Access
The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey
Amin Zadeh Shirazi, Eric Fornaciari, Mark D. McDonnell, et al.
Journal of Personalized Medicine (2020) Vol. 10, Iss. 4, pp. 224-224
Open Access | Times Cited: 47
RETRACTED ARTICLE: Automated brain tumor detection and segmentation using modified UNet and ResNet model
Nandyala Bindu, Panyam Narahari Sastry
Soft Computing (2023) Vol. 27, Iss. 13, pp. 9179-9189
Closed Access | Times Cited: 14
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
A knowledge-driven feature learning and integration method for breast cancer diagnosis on multi-sequence MRI
Hongwei Feng, Jiaqi Cao, Hongyu Wang, et al.
Magnetic Resonance Imaging (2020) Vol. 69, pp. 40-48
Closed Access | Times Cited: 37
MRI-based brain tumor detection using the fusion of histogram oriented gradients and neural features
Rafid Mostafiz, Mohammad Shorif Uddin, Nur-A- Alam, et al.
Evolutionary Intelligence (2021) Vol. 14, Iss. 2, pp. 1075-1087
Closed Access | Times Cited: 29
An approach for brain tumor detection using optimal feature selection and optimized deep belief network
T. Sathies Kumar, C. Arun, P. Ezhumalai
Biomedical Signal Processing and Control (2021) Vol. 73, pp. 103440-103440
Closed Access | Times Cited: 25
AI-Based Glioma Grading for a Trustworthy Diagnosis: An Analytical Pipeline for Improved Reliability
Carla Pitarch, Vicent Ribas, Alfredo Vellido
Cancers (2023) Vol. 15, Iss. 13, pp. 3369-3369
Open Access | Times Cited: 8
Review, Limitations, and future prospects of neural network approaches for brain tumor classification
Surajit Das, Rajat Subhra Goswami
Multimedia Tools and Applications (2023) Vol. 83, Iss. 15, pp. 45799-45841
Closed Access | Times Cited: 7
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
Alessandro Crimi, Spyridon Bakas, Hugo J. Kuijf, et al.
Lecture notes in computer science (2019)
Open Access | Times Cited: 20
An intelligent brain tumor segmentation using improved Deep Learning Model Based on Cascade Regression method
Deepak V.K, R. Sarath
Multimedia Tools and Applications (2022) Vol. 82, Iss. 13, pp. 20059-20078
Closed Access | Times Cited: 9
Machine and Deep Learning Approaches For Brain Tumor Identification: Technologies, Applications, and Future Directions
Vikram Verma, Alankrita Aggarwal, Tajinder Kumar
2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) (2023), pp. 392-399
Closed Access | Times Cited: 3
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