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The Impact of Resampling and Denoising Deep Learning Algorithms on Radiomics in Brain Metastases MRI
2021
Cancers
Magnetic resonance imaging (MRI) is predominant in the therapeutic management of cancer patients, unfortunately, patients have to wait a long time to get an appointment for examination. Therefore, new MRI devices include deep-learning (DL) solutions to save acquisition time. However, the impact of these algorithms on intensity and texture parameters has been poorly studied. The aim of this study was to evaluate the impact of resampling and denoising DL models on radiomics. Methods: Resampling
doi:10.3390/cancers14010036
pmid:35008198
pmcid:PMC8750741
fatcat:nlcxinmpxrff7ln3qzehnm7tpy