Synthetic lung ultrasound data generation using autoencoder with generative adversarial network

The goal of this study is to test the applicability of a generative adversarial network (GAN) to solve the class unbalancing problem in lung ultrasound (LUS) data. We introduce a supervised autoencoder with conditional latent space. During training, the generator utilizes the weights of the decoder...

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Veröffentlicht in:	The Journal of the Acoustical Society of America 2023-03, Vol.153 (3_supplement), p.A190-A190
Hauptverfasser:	Fatima, Noreen, Inchingolo, Riccardo, Smargiassi, Andrea, Soldati, Gino, Torri, Elena, Perrone, Tiziano, Demi, Libertario
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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