  Recent observations have shown that protoplanetary disks around young stars
can embed a wide variety of features. Raw disk images produced by high-contrast
imaging instruments are corrupted by slowly varying residual stellar light in
the form of quasi-static speckles. Hence, image processing is required to
remove speckles from images and to recover circumstellar signals. Current
algorithms that rely on the mainstream angular differential imaging (ADI)
observing technique are however limited by geometrical biases, and therefore
face a major challenge to reliably infer the morphology of extended disk
features. In the last two years, four algorithms have been developed for this
task, with three of them based on inverse problem (IP) approaches: REXPACO,
MAYONNAISE, and \MUSTARD. In this presentation, we will (i) present the new
MUSTARD algorithm and (ii) discuss the advantages of IP compared to others
methods based on systematic tests.
