Data completion is needed in dual‐source, dual‐energy computed tomography (CT) when physical or hardware constraints limit the field of view (FoV) covered by one of two imaging chains. Here we published a new Deep Learning approach for Spectral Extrapolation!
We have created an image processing pipeline for high-throughput, reduced-bias segmentation of multiparametric tumor MRI data and radiomics analysis, to better our understanding of preclinical imaging and the insights it provides when studying new cancer therapies.
Our mission is to develop, optimize and apply novel CT and MRI quantitative imaging at both preclinical and clinical levels !
