Medical imaging is seeking new image reconstruction approaches, producing a more accurate assessment of the informational content and an ever-shorter computation time. In this context, we are contributing in four major imaging modalities:
- ultrasound to achieve high frame rate imaging (near 1500 f/s) with good image quality based on deep learning-based approach;
- spectral photon-counting CT to investigate joint reconstruction and decomposition using deep learning techniques to improve the precision of spectral decomposition with reduced noise;
- diffusion Tensor MR images (DT-MRI) to improve the reconstruction of tiny structures such as brain white matter pathways by working on the optimization of the acquisition parameters;
- MRI for 3D blood measurements in large volumes to improve spatial resolution and quantification by optimizing the under-sampling strategies in terms of efficiency.