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Deep generative models have emerged as a promising approach in the medical image domain to address data scarcity.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Data augmentation generative adversarial networks
Antreas Antoniou, Amos Storkey, and Harrison Edwards · 2017
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End-to-end adversarial retinal image synthesis
Pedro Costa, Adrian Galdran, Maria Ines Meyer, Meindert Niemeijer, Michael Abràmoff, Ana Maria Mendonça, and Aurélio Campilho · 2017
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Medical image synthesis with context-aware generative adversarial networks
Dong Nie, Roger Trullo, Jun Lian, Caroline Petitjean, Su Ruan, Qian Wang, and Dinggang Shen · 2017
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Gan augmentation: Augmenting training data using generative adversarial networks
Christopher Bowles, Liang Chen, Ricardo Guerrero, Paul Bentley, Roger Gunn, Alexander Hammers, David Alexander Dickie, Maria Valdés Hernández, Joanna Wardlaw, and Daniel Rueckert · 2018
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Generative adversarial network for medical images (mi-gan)
Talha Iqbal and Hazrat Ali · 2018
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A respiratory sound database for the development of automated classification
BM Rocha, Dimitris Filos, L Mendes, Ioannis Vogiatzis, Eleni Perantoni, E Kaimakamis, P Natsiavas, Ana Oliveira, C Jácome, A Marques, et al · 2018
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Medical image synthesis for data augmentation and anonymization using generative adversarial networks
Hoo-Chang Shin, Neil A Tenenholtz, Jameson K Rogers, Christopher G Schwarz, Matthew L Senjem, Jeffrey L Gunter, Katherine P Andriole, and Mark Michalski · 2018
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Towards eeg generation using gans for bci applications
Fatemeh Fahimi, Zhuo Zhang, Wooi Boon Goh, Kai Keng Ang, and Cuntai Guan · 2019
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Synthesizing diverse lung nodules wherever massively: 3d multi-conditional gan-based ct image augmentation for object detection
Changhee Han, Yoshiro Kitamura, Akira Kudo, Akimichi Ichinose, Leonardo Rundo, Yujiro Furukawa, Kazuki Umemoto, Yuanzhong Li, and Hideki Nakayama · 2019
Cited alongside, same era.
Data augmentation using generative adversarial networks (cyclegan) to improve generalizability in ct segmentation tasks
Veit Sandfort, Ke Yan, Perry J Pickhardt, and Ronald M Summers · 2019
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Medgan: Medical image translation using gans
Karim Armanious, Chenming Jiang, Marc Fischer, Thomas Küstner, Tobias Hepp, Konstantin Nikolaou, Sergios Gatidis, and Bin Yang · 2020
Cited alongside, same era.
Synsiggan: Generative adversarial networks for synthetic biomedical signal generation
Debapriya Hazra and Yung-Cheol Byun · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Conditional gan based augmentation for predictive modeling of respiratory signals
S Jayalakshmy and Gnanou Florence Sudha · 2021
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Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2021
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Data augmentation using generative adversarial networks (gans) for gan-based detection of pneumonia and covid-19 in chest x-ray images
Saman Motamed, Patrik Rogalla, and Farzad Khalvati · 2021
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Three-dimensional medical image synthesis with denoising diffusion probabilistic models
Zolnamar Dorjsembe, Sodtavilan Odonchimed, and Furen Xiao · 2022
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Supervised contrastive learning for respiratory sound classification
Ilyass Moummad and Nicolas Farrugia · 2022
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Generative adversarial networks for respiratory sound augmentation
Kirill Kochetov and Andrey Filchenkov · 2020
Cited alongside, same era.
Within the lack of chest covid-19 x-ray dataset: a novel detection model based on gan and deep transfer learning
Mohamed Loey, Florentin Smarandache, and Nour Eldeen M. Khalifa · 2020
Cited alongside, same era.
Synthesis of normal heart sounds using generative adversarial networks and empirical wavelet transform
Pedro Narváez and Winston S Percybrooks · 2020
Cited alongside, same era.
Generating electrocardiogram signals by deep learning
Naren Wulan, Wei Wang, Pengzhong Sun, Kuanquan Wang, Yong Xia, and Henggui Zhang · 2020
Cited alongside, same era.
Respirenet: A deep neural network for accurately detecting abnormal lung sounds in limited data setting
Siddhartha Gairola, Francis Tom, Nipun Kwatra, and Mohit Jain · 2021
Cited alongside, same era.
AST: Audio Spectrogram Transformer
Yuan Gong, Yu-An Chung, and James Glass · 2021
Cited alongside, same era.
Lung sound classification using co-tuning and stochastic normalization
Truc Nguyen and Franz Pernkopf · 2022
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Data augmentation using variational autoencoders for improvement of respiratory disease classification
Jane Saldanha, Shaunak Chakraborty, Shruti Patil, Ketan Kotecha, Satish Kumar, and Anand Nayyar · 2022
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A domain transfer based data augmentation method for automated respiratory classification
Zijie Wang and Zhao Wang · 2022
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Diffusion models for medical anomaly detection
Julia Wolleb, Florentin Bieder, Robin Sandkühler, and Philippe C Cattin · 2022
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Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Sangmin Bae, June-Woo Kim, Won-Yang Cho, Hyerim Baek, Soyoun Son, Byungjo Lee, Changwan Ha, Kyongpil Tae, Sungnyun Kim, and Se-Young Yun · 2023
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Dual-encoder vae-gan with spatiotemporal features for emotional eeg data augmentation
Chenxi Tian, Yuliang Ma, Jared Cammon, Feng Fang, Yingchun Zhang, and Ming Meng · 2023
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