Performance analysis of GAN approaches in the portable chest X-ray synthetic image generation for COVID-19 screening
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Performance analysis of GAN approaches in the portable chest X-ray synthetic image generation for COVID-19 screeningAutor(es)
Data
2022Cita bibliográfica
D. I. Morís, M. Gende, J. de Moura, J. Novo, M. Ortega, "Performance analysis of GAN approaches in the portable chest X-ray synthetic image generation for COVID-19 screening", 18th International Conference on Computer Aided Systems Theory - EUROCAST'22, 108-109, Las Palmas de Gran Canaria, Spain, 2022
Resumo
[Abstract]: This manuscript presents a performance analysis of chest Xray synthetic image generation for COVID-19 screening. The proposed system translates chest X-ray images from Normal to COVID-19 and vice versa, without needing paired data, representing a powerful data augmentation approach. To this end, we analyze the performance of 3 representative state of the art architectures for image translation, assessing the impact of oversampling on improving the performance of automatic COVID-19 screening.
Palabras chave
Computer-aided Diagnosis
Portable Chest X-ray
COVID-19
Deep Learning
Synthetic Image Generation
Portable Chest X-ray
COVID-19
Deep Learning
Synthetic Image Generation
Descrición
Versión aceptada de: D. I. Morís, M. Gende, J. de Moura, J. Novo, M. Ortega, "Performance analysis of GAN approaches in the portable chest X-ray synthetic image generation for COVID-19 screening", 18th International Conference on Computer Aided Systems Theory - EUROCAST'22, 108-109, Las Palmas de Gran Canaria, Spain, 2022 Extended abstracts
ISBN
978-84-09-38381-8