Article

Synthetic Genitourinary Image Synthesis via Generative Adversarial Networks: Enhancing AI Diagnostic Precision

2024-05-21

Abstract excerpt

In the realm of computational pathology, the scarcity and restricted diversity of genitourinary (GU) tissue datasets pose significant challenges for training robust diagnostic models. This study explores the potential of Generative Adversarial Networks (GANs) to mitigate these limitations by generating high-quality synthetic images of rare or underrepresented GU tissues. We hypothesized that augmenting the trainin...

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Literature Corpus work: a82863ae-c7ff-570d-a71a-5e7cd1487399
DOI: 10.1101/2024.05.20.595002

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