Fetching the paper…
Reading the bibliography…
While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients.
Cross-validatory choice and assessment of statistical predictions
Stone, M.: · 1974
Earlier work this paper cites.
The dynamic representation of scenes
Rensink, R.A.: · 2000
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K., Vedaldi, A., Zisserman, A.: · 2013
Earlier work this paper cites.
Deep learning based imaging data completion for improved brain disease diagnosis
Li, R., Zhang, W., Suk, H.I., Wang, L., Li, J., Shen, D., Ji, S.: · 2014
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: · 2014
Earlier work this paper cites.
Prediction of standard-dose brain pet image by using mri and low-dose brain [18f] fdg pet images
Kang, J., Gao, Y., Shi, F., Lalush, D.S., Lin, W., Shen, D.: · 2015
Earlier work this paper cites.
Estimating ct image from mri data using structured random forest and auto-context model
Huynh, T., Gao, Y., Kang, J., Wang, L., Zhang, P., Lian, J., Shen, D.: · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., Brox, T.: · 2015
Earlier work this paper cites.
The application of two-level attention models in deep convolutional neural network for fine-grained image classification
Xiao, T., Xu, Y., Yang, K., Zhang, J., Peng, Y., Zhang, Z.: · 2015
Earlier work this paper cites.
Estimating ct image from mri data using 3d fully convolutional networks
Nie, D., Cao, X., Gao, Y., Wang, L., Shen, D.: · 2016
Earlier work this paper cites.
Learning deep features for discriminative localization
Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., Torralba, A.: · 2016
Earlier work this paper cites.
Attention to scale: Scale-aware semantic image segmentation
Chen, L.C., Yang, Y., Wang, J., Xu, W., Yuille, A.L.: · 2016
Earlier work this paper cites.
Tree-to-sequence attentional neural machine translation
Eriguchi, A., Hashimoto, K., Tsuruoka, Y.: · 2016
Earlier work this paper cites.
Zagoruyko, S., Komodakis, N.: · 2016
Cited alongside, same era.
Image-to-image translation with conditional adversarial networks
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: · 2017
Cited alongside, same era.
Unsupervised image-to-image translation networks
Liu, M.Y., Breuel, T., Kautz, J.: · 2017
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Zhu, J.Y., Park, T., Isola, P., Efros, A.A.: · 2017
Cited alongside, same era.
Toward multimodal image-to-image translation
Zhu, J.Y., Zhang, R., Pathak, D., Darrell, T., Efros, A.A., Wang, O., Shechtman, E.: · 2017
Cited alongside, same era.
Mr-based synthetic ct generation using a deep convolutional neural network method
Synthesizing missing pet from mri with cycle-consistent generative adversarial networks for alzheimer’s disease diagnosis
Pan, Y., Liu, M., Lian, C., Zhou, T., Xia, Y., Shen, D.: · 2018
Later among the works it cites.
Generating synthetic cts from magnetic resonance images using generative adversarial networks
Gehari, H.E., Nejad-Davarani, S., Dong, M., Glide-Hurst, C.: · 2018
Later among the works it cites.
Unsupervised attention-guided image-to-image translation
Mejjati, Y.A., Richardt, C., Tompkin, J., Cosker, D., Kim, K.I.: · 2018
Later among the works it cites.
Attention-gan for object transfiguration in wild images
Chen, X., Xu, C., Yang, X., Tao, D.: · 2018
Later among the works it cites.
Jetley, S., Lord, N.A., Lee, N., Torr, P.H.: · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Han, X.: · 2017
Cited alongside, same era.
Medical image synthesis with context-aware generative adversarial networks
Nie, D., Trullo, R., Lian, J., Petitjean, C., Ruan, S., Wang, Q., Shen, D.: · 2017
Cited alongside, same era.
Deep mr to ct synthesis using unpaired data
Wolterink, J.M., Dinkla, A.M., Savenije, M.H., Seevinck, P.R., van den Berg, C.A., Išgum, I.: · 2017
Cited alongside, same era.
A structured self-attentive sentence embedding
Lin, Z., Feng, M., Santos, C.N.d., Yu, M., Xiang, B., Zhou, B., Bengio, Y.: · 2017
Cited alongside, same era.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Choi, Y., Choi, M., Kim, M., Ha, J.W., Kim, S., Choo, J.: · 2018
Cited alongside, same era.
Multimodal unsupervised image-to-image translation
Huang, X., Liu, M.Y., Belongie, S., Kautz, J.: · 2018
Cited alongside, same era.
Image to image translation for domain adaptation
Murez, Z., Kolouri, S., Kriegman, D., Ramamoorthi, R., Kim, K.: · 2018
Cited alongside, same era.
Zhang, H., Goodfellow, I., Metaxas, D., Odena, A.: · 2018
Later among the works it cites.
Multi-step power consumption forecasting in thailand using dual-stage attentional lstm
Siridhipakul, C., Vateekul, P.: · 2019
Later among the works it cites.
Attention-guided generative adversarial network to address atypical anatomy in modality transfer
Emami, H., Dong, M., Glide-Hurst, C.K.: · 2020
Closest in time.
Medgan: Medical image translation using gans
Armanious, K., Jiang, C., Fischer, M., Küstner, T., Hepp, T., Nikolaou, K., Gatidis, S., Yang, B.: · 2020
Closest in time.
Attention-guided generative adversarial network to address atypical anatomy in synthetic ct generation
Emami, H., Dong, M., Glide-Hurst, C.K.: · 2020
Closest in time.
Spa-gan: Spatial attention gan for image-to-image translation
Emami, H., Aliabadi, M.M., Dong, M., Chinnam, R.: · 2020
Closest in time.
Attention-based recurrent neural network for multistep-ahead prediction of process performance
Aliabadi, M.M., Emami, H., Dong, M., Huang, Y.: · 2020
Closest in time.