  Medical imaging is an invaluable resource in medicine as it enables to peer
inside the human body and provides scientists and physicians with a wealth of
information indispensable for understanding, modelling, diagnosis, and
treatment of diseases. Reconstruction algorithms entail transforming signals
collected by acquisition hardware into interpretable images. Reconstruction is
a challenging task given the ill-posed of the problem and the absence of exact
analytic inverse transforms in practical cases. While the last decades
witnessed impressive advancements in terms of new modalities, improved temporal
and spatial resolution, reduced cost, and wider applicability, several
improvements can still be envisioned such as reducing acquisition and
reconstruction time to reduce patient's exposure to radiation and discomfort
while increasing clinics throughput and reconstruction accuracy. Furthermore,
the deployment of biomedical imaging in handheld devices with small power
requires a fine balance between accuracy and latency.
