The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
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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
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
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
Indoor segmentation and support inference from rgbd images
Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760
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 with Deep Neural Networks
Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.05.004 · Cited by 3,278
Training Region-Based Object Detectors with Online Hard Example Mining
Shrivastava, A., Gupta, A., & Girshick, R. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.89 · Cited by 2,686
Is Faster R-CNN Doing Well for Pedestrian Detection?
Zhang, L., Lin, L., Liang, X., & He, K. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46475-6_28 · Cited by 852
Holistically-nested edge detection
Xie, S., & Tu, Z. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-017-1004-z · Cited by 682
Cited by
Digital pathology and artificial intelligence
Niazi, M. K. K., Parwani, A. V., & Gurcan, M. N. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30154-8 · Cited by 1,232
Salvi, M., Acharya, U. R., Molinari, F., & Meiburger, K. M. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.104129 · Cited by 386
Artificial intelligence for digital and computational pathology
Song, A. H., Jaume, G., Williamson, D. F. K., Lu, M. Y., Vaidya, A., Miller, T. R., & Mahmood, F. (2023) · Nature Reviews Bioengineering · doi:10.1038/s44222-023-00096-8 · Cited by 356
Literature review: efficient deep neural networks techniques for medical image analysis
Abdou, M. A. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-06960-9 · Cited by 312
Faes, L., Wagner, S. K., Fu, D. J., Liu, X., Korot, E., Ledsam, J. R., Back, T., Chopra, R., Pontikos, N., Kern, C., et al. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30108-6 · Cited by 308
Metadata
- Authors
- Li, C., Wang, X., Liu, W., & Latecki, L. J.
- Venue
- Medical Image Analysis
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 45
- Pages
- 121-133
- ISSN
- 1361-8415 (ISSN-L)
- OpenAlex
- W2789755511
- Cited by
- 190
- References
- 9
- FWCI
- 12.87
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks. https://app.cochat.ai/papers/10.1016/j.media.2017.12.002
- The paper
- Li, C., Wang, X., Liu, W., & Latecki, L. J. (2018). DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks. Medical Image Analysis. https://doi.org/10.1016/j.media.2017.12.002
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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.
