Abstract
This thesis 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.
Original language | English |
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Award date | 3 Jul 2023 |
Place of Publication | Maastricht |
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Publication status | Published - 2023 |
Keywords
- generative models
- radiomics
- low dose CTs
- features’ reproducibility and performance