Exploring Bioimage Synthesis and Detection via Generative Adversarial Networks: A Multi-Faceted Case Study

Exploring Bioimage Synthesis and Detection via Generative Adversarial Networks: A Multi-Faceted Case Study

Background:Generative Adversarial Networks (GANs), thanks to their great versatility, have a plethora of applications in biomedical imaging with the goal of simulating complex pathological conditions and creating clinical data used for training advanced machine learning models. The ability to genera...

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Bibliographic Details
Main Authors: Valeria Sorgente, Dante Biagiucci, Mario Cesarelli, Luca Brunese, Antonella Santone, Fabio Martinelli, Francesco Mercaldo
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Journal of Imaging
Subjects:
GAN
convolutional generative adversarial network
DCGAN
deep convolutional generative adversarial network
deep learning
bioimages
Online Access:https://www.mdpi.com/2313-433X/11/7/214
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