The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Overview of deep learning in medical imaging
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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
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Backpropagation Applied to Handwritten Zip Code Recognition
LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989) · Neural Computation · doi:10.1162/neco.1989.1.4.541 · Cited by 11,891
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Computer-aided diagnosis in medical imaging: historical review, current status and future potential
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Cited by
An overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058
TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images
Wasserthal, J., Breit, H.-C., Meyer, M. T., Pradella, M., Hinck, D., Sauter, A. W., Heye, T., Boll, D. T., Cyriac, J., Yang, S., et al. (2023) · Radiology: Artificial Intelligence · doi:10.1148/ryai.230024 · Cited by 1,657
Deep Learning in Medical Ultrasound Analysis: A Review
Liu, S., Wang, Y., Yang, X., Lei, B., Liu, L., Li, S. X., Ni, D., & Wang, T. (2019) · Engineering · doi:10.1016/j.eng.2018.11.020 · Cited by 798
A survey on active learning and human-in-the-loop deep learning for medical image analysis
Budd, S., Robinson, E. C., & Kainz, B. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102062 · Cited by 606
Real-world data: A brief review of the methods, applications, challenges and opportunities
Liu, F., & Panagiotakos, D. (2022) · BMC Medical Research Methodology · doi:10.1186/s12874-022-01768-6 · Cited by 496
Metadata
- Authors
- Suzuki, K.
- Venue
- Radiological Physics and Technology
- Published
- 2017-07-08
- Volume
- 10
- Issue
- 3
- Pages
- 257-273
- ISSN
- 1865-0333 (ISSN-L)
- 1865-0341
- OpenAlex
- W2731899572
- Cited by
- 1,087
- References
- 13
- FWCI
- 26.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Suzuki, K. (2017). Overview of deep learning in medical imaging. Radiological Physics and Technology. https://doi.org/10.1007/s12194-017-0406-5
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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.
