Generative Models Improve Radiomics Reproducibility and Performance in Low Dose CTs

In this thesis Junhua focused on using generative models to improve radiomics reproducibility and performance in low-dose CTs. Different generative models were included as testing models, and models were trained based on paired simulation data and unpaired real data. Before delving into the story of low-dose CT radiomics enhancement, this thesis investigated some details about generative models for low-dose denoising and applied low-dose CT radiomics to a new application. The results showed that low-dose CT radiomics achieved good performance in the new applications, and generative models can improve radiomics reproducibility and performance in low-dose CTs.

Congratulations to doctor Junhua Chen for obtaining his PhD supervised by Andre Dekker, Leonard Wee and Inigo Bermejo.

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The link to his thesis, please click here.