The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV
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Citations
Cites
Deep Attentional Features for Prostate Segmentation in Ultrasound
Wang, Y., Deng, Z., Hu, X., Zhu, L., Yang, X., Xu, X., Heng, P., & Ni, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_60 · Cited by 144
Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations
Bai, W., Suzuki, H., Qin, C., Tarroni, G., Oktay, O., Matthews, P. M., & Rueckert, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_67 · Cited by 141
AtlasNet: Multi-atlas Non-linear Deep Networks for Medical Image Segmentation
Vakalopoulou, M., Chassagnon, G., Bus, N., Marini, R., Zacharaki, E. I., Revel, M., & Nikos Paragios, A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_75 · Cited by 85
Real-Time Prediction of Segmentation Quality
Robinson, R., Oktay, O., Bai, W., Valindria, V. V., Sanghvi, M. M., Aung, N., Paiva, J. M., Zemrak, F., Fung, K., Lukaschuk, E. I., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_66 · Cited by 71
Cai, J., Tang, Y., Lü, L., Harrison, A. P., Yan, K., Xiao, J. Z., Yang, L., & Summers, R. M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_46 · Cited by 66
Inter-site Variability in Prostate Segmentation Accuracy Using Deep Learning
Gibson, E., Hu, Y., Ghavami, N., Ahmed, H. U., Moore, C. M., Emberton, M., Huisman, H. J., & Barratt, D. C. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_58 · Cited by 66
Hajek, J., Unberath, M., Fotouhi, J., Bier, B., Lee, S. C., Osgood, G. M., Maier, A., Armand, M., & Navab, N. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_35 · Cited by 52
Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy Using Deep Learning
Zia, A., Hung, A. J., Essa, I. A., & Jarc, A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_32 · Cited by 52
Ma, J., Lin, F., Wesarg, S., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_55 · Cited by 51
Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound
Degel, M., Navab, N., & Albarqouni, S. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3_72 · Cited by 47
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Bien, N., Rajpurkar, P., Ball, R. L., Irvin, J., Park, A., Jones, E., Bereket, M., Patel, B. N., Yeom, K. W., Shpanskaya, K., et al. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002699 · Cited by 734
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
Hosny, A., Parmar, C., Coroller, T. P., Grossmann, P., Zeleznik, R., Kumar, A., Bussink, J., Gillies, R. J., Mak, R. H., & Aerts, H. J. W. L. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002711 · Cited by 579
Metadata
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1651609297
- Cited by
- 1,048
- References
- 22
- FWCI
- 17.23
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV. https://app.cochat.ai/papers/10.1007/978-3-030-00937-3
- The paper
- Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV. (2018). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-00937-3
Data sources
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.
