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Performance analysis of GAN approaches in the portable chest X-ray synthetic image generation for COVID-19 screening

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URI: http://hdl.handle.net/2183/36468

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2022

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Iglesias Morís, Daniel

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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

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Abstract

[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.

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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
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Computer-aided Diagnosis Portable Chest X-ray COVID-19 Deep Learning Synthetic Image Generation

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