Fetching the paper…
Reading the bibliography…
Computed medical imaging systems require a computational reconstruction procedure for image formation.
Lustig, M., Donoho, D., and Pauly, J. M., “Sparse MRI: The application of compressed sensing for rapid MR imaging,” Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine
2007
Earlier work this paper cites.
Candès, E. J. and Wakin, M. B., “An introduction to compressive sampling,” IEEE signal processing magazine
2008
Earlier work this paper cites.
Chen, G.-H., Tang, J., and Leng, S., “Prior image constrained compressed sensing (piccs): a method to accurately reconstruct dynamic ct images from highly undersampled projection data sets,” Medical physics
2008
Earlier work this paper cites.
Barrett, H. H. and Myers, K. J., [ Foundations of image science
2013
Earlier work this paper cites.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y., “Generative adversarial nets,” in [ Advances in neural information processing systems
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al., “The multimodal brain tumor image segmentation benchmark (brats),” IEEE transactions on medical imaging
2014
Earlier work this paper cites.
Weizman, L., Eldar, Y. C., and Ben Bashat, D., “Reference-based mri,” Medical physics
2016
Cited alongside, same era.
2017
Cited alongside, same era.
Bora, A., Jalal, A., Price, E., and Dimakis, A. G., “Compressed sensing using generative models,” in [ Proceedings of the 34th International Conference on Machine Learning-Volume 70
2017
Cited alongside, same era.
Mota, J. F., Deligiannis, N., and Rodrigues, M. R., “Compressed sensing with prior information: Strategies, geometry, and bounds,” IEEE Transactions on Information Theory
2017
Cited alongside, same era.
2020
Later among the works it cites.
Asim, M., Daniels, G., Leong, O., Ahmed, A., and Hand, P., “Invertible generative models for inverse problems: mitigating representation error and dataset bias,” in [ Proceedings of the International Conference on Machine Learning
2020
Later among the works it cites.
Kelkar, V. A., Bhadra, S., and Anastasio, M. A., “Compressible latent-space invertible networks for generative model-constrained image reconstruction,” IEEE Transactions on Computational Imaging
2021
Later among the works it cites.
Bhadra, S., Kelkar, V. A., Brooks, F. J., and Anastasio, M. A., “On hallucinations in tomographic image reconstruction,” IEEE Transactions on Medical Imaging
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2018
Cited alongside, same era.
Karras, T., Laine, S., and Aila, T., “A style-based generator architecture for generative adversarial networks,” in [ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
2019
Cited alongside, same era.
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., and Aila, T., “Analyzing and improving the image quality of stylegan,” in [ Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
2020
Cited alongside, same era.
Jha, A. K., Myers, K. J., Obuchowski, N. A., Liu, Z., Rahman, M. A., Saboury, B., Rahmim, A., and Siegel, B. A., “Objective task-based evaluation of artificial intelligence-based medical imaging methods: Framework, strategies, and role of the physician,” PET clinics
2021
Later among the works it cites.
Zhang, X., Kelkar, V. A., Granstedt, J., Li, H., and Anastasio, M. A., “Impact of deep learning-based image super-resolution on binary signal detection,” Journal of Medical Imaging
2021
Later among the works it cites.