  Quality assessment is a key element for the evaluation of hardware and
software involved in image and video acquisition, processing, and
visualization. In the medical field, user-based quality assessment is still
considered more reliable than objective methods, which allow the implementation
of automated and more efficient solutions. Regardless of increasing research in
this topic in the last decade, defining quality standards for medical content
remains a non-trivial task, as the focus should be on the diagnostic value
assessed from expert viewers rather than the perceived quality from na\"{i}ve
viewers, and objective quality metrics should aim at estimating the first
rather than the latter. In this paper, we present a survey of methodologies
used for the objective quality assessment of medical images and videos,
dividing them into visual quality-based and task-based approaches. Visual
quality based methods compute a quality index directly from visual attributes,
while task-based methods, being increasingly explored, measure the impact of
quality impairments on the performance of a specific task. A discussion on the
limitations of state-of-the-art research on this topic is also provided, along
with future challenges to be addressed.
