Regularization in Fluorescence Microscopy and Photoacoustic Imaging

Structures imaged by fluorescence microscopy and photo-acoustic imaging (PAT) have a statistical distribution of high intensity and high curvature points that is distinct from the structures imaged under other modalities such as MRI and CT. We constructed a form of regularization functional that combines the image intensity and derivatives in a unique way, to exploit these specific characteristics, and applied it to image deblurring and reconstruction for PAT and fluorescence microscopy. Under the presence of a large amount of noise, we obtained significantly improved restoration/reconstruction compared to well known state-of-the-art regularization techniques.