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Image Reconstruction is a New Frontier of Machine Learning
Abstract
Over past several years, machine learning, or more generally artificial intelligence, has generated overwhelming research interest and attracted unprecedented public attention. As tomographic imaging researchers, we share the excitement from our imaging perspective [item 1) in the Appendix], and organized this special issue dedicated to the theme of "Machine learning for image reconstruction." This special issue is a sister issue of the special issue published in May 2016 of this journal with the theme "Deep learning in medical imaging" [item 2) in the Appendix]. While the previous special issue targeted medical image processing/analysis, this special issue focuses on data-driven tomographic reconstruction. These two special issues are highly complementary, since image reconstruction and image analysis are two of the main pillars for medical imaging. Together we cover the whole workflow of medical imaging: from tomographic raw data/features to reconstructed images and then extracted diagnostic features/readings.
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Citations
Cited by
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Self-citationLanglotz, C. P., Allen, B., Erickson, B. J., Kalpathy-Cramer, J., Bigelow, K., Cook, T. S., Flanders, A. E., Lungren, M. P., Mendelson, D. S., Rudie, J. D., et al. (2019) · Radiology · doi:10.1148/radiol.2019190613 · Cited by 368
Self-citationImplicit data crimes: Machine learning bias arising from misuse of public data
Shimron, E., Tamir, J. I., Wang, K., & Lustig, M. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2117203119 · Cited by 112
DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction
Liu, J., Anirudh, R., Thiagarajan, J. J., He, S., Mohan, K. A., Kamilov, U. S., & Kim, H. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00963 · Cited by 106
Deep-Learning-Based Few-Angle Cardiac SPECT Reconstruction Using Transformer
Xie, H., Thorn, S., Liu, Y.-H., Lee, S., Liu, Z., Wang, G., Sinusas, A. J., & Liu, C. (2023) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2022.3187595 · Cited by 16
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Metadata
- Authors
- Wang, G., Ye, J. C., Mueller, K., & Fessler, J. A.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2018-06
- Volume
- 37
- Issue
- 6
- Pages
- 1289-1296
- ISSN
- 0278-0062 (ISSN-L)
- 1558-254X
- OpenAlex
- W2803224943
- Cited by
- 525
- References
- 0
- FWCI
- 42.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, G., Ye, J. C., Mueller, K., & Fessler, J. A. (2018). Image Reconstruction is a New Frontier of Machine Learning. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/tmi.2018.2833635
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