The DOI matches its Crossref record; 163 of the 163 references it cites were found in a registry or an index.
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Rethinking the Inception Architecture for Computer Vision
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Focal Loss for Dense Object Detection
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Cited by
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation
Tajbakhsh, N., Jeyaseelan, L., Li, Q., Chiang, J. N., Wu, Z., & Ding, X. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101693 · Cited by 1,095
“work of Karimi et al. (2019) that primarily considers label noise in the medical image datasets.”
BackgroundDeep semantic segmentation of natural and medical images: a review
Asgari Taghanaki, S., Abhishek, K., Cohen, J. P., Cohen-Adad, J., & Hamarneh, G. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-020-09854-1 · Cited by 870
Federated learning for medical image analysis: A survey
Guan, H., Yap, P.-T., Bozoki, A., & Liu, M. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110424 · Cited by 518
A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images
Wang, G., Liu, X., Li, C., Xu, Z., Ruan, J., Zhu, H., Meng, T., Li, K., Huang, N., & Zhang, S. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3000314 · Cited by 469
Machine learning and deep learning approach for medical image analysis: diagnosis to detection
Rana, M., & Bhushan, M. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-022-14305-w · Cited by 365
Metadata
- Authors
- Karimi, D., Dou, H., Warfield, S. K., & Gholipour, A.
- Venue
- Medical Image Analysis
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 65
- Pages
- 101759
- ISSN
- 1361-8415 (ISSN-L)
- OpenAlex
- W2992232939
- Cited by
- 706
- References
- 163
- FWCI
- 34.57
- Type
- journal article
- Language
- en
- Open access
- green
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- Karimi, D., Dou, H., Warfield, S. K., & Gholipour, A. (2020). Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis. Medical Image Analysis. https://doi.org/10.1016/j.media.2020.101759
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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