MALIN and the new computational imaging & learning research unit

Luca Calatroni, a UniGe lecturer in computer science, is principal investigator of MALIN (model-aware learning for imaging inverse problems in fluorescence microscopy), a European project funded by an ERC starting grant of €1.5 million. MALIN addresses one of the most complex challenges in scientific imaging: the reconstruction of fluorescence microscopy images from incomplete, undersampled and interference (noise) affected data.

The full article is in the Academic Magazine.