The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Deep Multi-Scale 3D Convolutional Neural Network (CNN) for MRI Gliomas Brain Tumor Classification
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Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary
Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella-Branger, D., Cavenee, W. K., Ohgaki, H., Wiestler, O. D., Kleihues, P., & Ellison, D. W. (2016) · Acta Neuropathologica · doi:10.1007/s00401-016-1545-1 · Cited by 15,657
The 2007 WHO Classification of Tumours of the Central Nervous System
Louis, D. N., Ohgaki, H., Wiestler, O. D., Cavenee, W. K., Burger, P. C., Jouvet, A., Scheithauer, B. W., & Kleihues, P. (2007) · Acta Neuropathologica · doi:10.1007/s00401-007-0243-4 · Cited by 15,397
The multimodal brain tumor image segmentation benchmark (BRATS)
Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2377694 · Cited by 6,781
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012) · arXiv · doi:10.48550/arxiv.1207.0580 · Cited by 6,382
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
Kamnitsas, K., Ledig, C., Newcombe, V. F. J., Simpson, J. P., Kane, A. D., Menon, D. K., Rueckert, D., & Glocker, B. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.10.004 · Cited by 3,498
Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images
Pereira, S., Pinto, A., Alves, V., & Silva, C. A. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2538465 · Cited by 2,735
The Effectiveness of Data Augmentation in Image Classification using Deep Learning
Perez, L., & Wang, J. (2017) · arXiv · doi:10.48550/arxiv.1712.04621 · Cited by 2,499
Cited by
A decision support system for multimodal brain tumor classification using deep learning
Sharif, M. I., Khan, M. A., Alhussein, M., Aurangzeb, K., & Raza, M. (2022) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00321-0 · Cited by 305
Brain Tumor Detection and Classification Using Intelligence Techniques: An Overview
Solanki, S., Singh, U. P., Chouhan, S. S., & Jain, S. (2023) · IEEE Access · doi:10.1109/access.2023.3242666 · Cited by 259
Multiclass classification of brain tumors using a novel CNN architecture
Kibriya, H., Masood, M., Nawaz, M., & Nazir, T. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12977-y · Cited by 72
The aspects of running artificial intelligence in emergency care; a scoping review
(2023) · Archives of Academic Emergency Medicine · doi:10.22037/aaem.v11i1.1974 · Cited by 45
Laçi, H., Sevrani, K., & Iqbal, S. (2025) · BMC Medical Imaging · doi:10.1186/s12880-025-01701-5 · Cited by 24
Metadata
- Authors
- Mzoughi, H., Njeh, I., Wali, A., Slima, M. B., BenHamida, A., Mhiri, C., & Mahfoudhe, K. B.
- Venue
- Journal of Digital Imaging
- Published
- 2020-05-21
- Volume
- 33
- Issue
- 4
- Pages
- 903-915
- ISSN
- 0897-1889 (ISSN-L)
- 1618-727X
- OpenAlex
- W3027411515
- Cited by
- 361
- References
- 40
- FWCI
- 14.66
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Mzoughi, H., Njeh, I., Wali, A., Slima, M. B., BenHamida, A., Mhiri, C., & Mahfoudhe, K. B. (2020). Deep Multi-Scale 3D Convolutional Neural Network (CNN) for MRI Gliomas Brain Tumor Classification. Journal of Digital Imaging. https://doi.org/10.1007/s10278-020-00347-9
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
