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Pulmonary opacification is the inflammation in the lungs caused by many respiratory ailments, including the novel corona virus disease 2019 (COVID-19).
The acute respiratory distress syndrome
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Marked point process in image analysis
Descombes, X. and Zerubia, J · 2002
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Diagnosis and testing in bronchiolitis: a systematic review
Bordley, W. C., Viswanathan, M., King, V. J., Sutton, S. F., Jackman, A. M., Sterling, L., and Lohr, K. N · 2004
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Random erasing data augmentation
Zhong, Z., Zheng, L., Kang, G., Li, S., and Yang, Y · 2005
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Extracting and composing robust features with denoising autoencoders
Vincent, P., Larochelle, H., Bengio, Y., and Manzagol, P.-A · 2008
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An edge-region force guided active shape approach for automatic lung field detection in chest radiographs
Xu, T., Mandal, M., Long, R., Cheng, I., and Basu, A · 2012
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Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration
Candemir, S., Jaeger, S., Palaniappan, K., Musco, J. P., Singh, R. K., Xue, Z., Karargyris, A., Antani, S., Thoma, G., and McDonald, C. J · 2013
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Two public chest x-ray datasets for computer-aided screening of pulmonary diseases
Jaeger, S., Candemir, S., Antani, S., Wáng, Y.-X. J., Lu, P.-X., and Thoma, G · 2014
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Kingma, D. and Ba, J · 2014
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2014
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Robust learning under uncertain test distributions: Relating covariate shift to model misspecification
Wen, J., Yu, C.-N., and Greiner, R · 2014
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Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., and Darrell, T · 2015
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T · 2015
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Learning to read chest x-rays: Recurrent neural cascade model for automated image annotation
Shin, H.-C., Roberts, K., Lu, L., Demner-Fushman, D., Yao, J., and Summers, R. M · 2016
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Structure correcting adversarial network for chest x-rays organ segmentation, September 27 2018
Dai, W., Liang, X., Zhang, H., Xing, E., and Doyle, J · 2018
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A variational U-net for conditional appearance and shape generation
Esser, P., Sutter, E., and Ommer, B · 2018
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Non-adversarial mapping with VAEs
Hoshen, Y · 2018
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Nam: Non-adversarial unsupervised domain mapping
Hoshen, Y. and Wolf, L · 2018
Pytorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al · 2019
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A survey on image data augmentation for deep learning
Shorten, C. and Khoshgoftaar, T. M · 2019
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An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks
Souza, J. C., Diniz, J. O. B., Ferreira, J. L., da Silva, G. L. F., Silva, A. C., and de Paiva, A. C · 2019
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XLSor: A robust and accurate lung segmentor on chest X-rays using criss-cross attention and customized radiorealistic abnormalities generation
Tang, Y., Tang, Y., Xiao, J., and Summers, R. M · 2019
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Carbontracker: Tracking and predicting the carbon footprint of training deep learning models
Anthony, L. F. W., Kanding, B., and Selvan, R · 2020
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3d mri brain tumor segmentation using autoencoder regularization
Myronenko, A · 2018
Cited alongside, same era.
Handling incomplete heterogeneous data using vaes
Nazabal, A., Olmos, P. M., Ghahramani, Z., and Valera, I · 2018
Cited alongside, same era.
A review on lung boundary detection in chest x-rays
Candemir, S. and Antani, S · 2019
Cited alongside, same era.
Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al · 2019
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Revisiting self-supervised visual representation learning
Kolesnikov, A., Zhai, X., and Beyer, L · 2019
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Variational image inpainting
Ham, C., Raj, A., Cartillier, V., and Essa, I
Cited in the paper.
Covid-19 image data collection, 2020
Cohen, J. P · 2020
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Covid-19 image data collection
Cohen, J. P., Morrison, P., and Dao, L · 2020
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Portable chest x-ray in coronavirus disease-19 (covid-19): A pictorial review
Jacobi, A., Chung, M., Bernheim, A., and Eber, C · 2020
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Covid-19 identification in chest x-ray images on flat and hierarchical classification scenarios
Pereira, R. M., Bertolini, D., Teixeira, L. O., Silla Jr, C. N., and Costa, Y. M · 2020
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Radiological findings from 81 patients with covid-19 pneumonia in wuhan, china: a descriptive study
Shi, H., Han, X., Jiang, N., Cao, Y., Alwalid, O., Gu, J., Fan, Y., and Zheng, C · 2020
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Frequency and distribution of chest radiographic findings in covid-19 positive patients
Wong, H. Y. F., Lam, H. Y. S., Fong, A. H.-T., Leung, S. T., Chin, T. W.-Y., Lo, C. S. Y., Lui, M. M.-S., Lee, J. C. Y., Chiu, K. W.-H., Chung, T., et al · 2020
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