Guest Editorial Large-Scale Medical Image and Video Analytics for Clinical Decision Support

The papers in this special section focus on large-scale medical imaging and video analytics for clinical decision support systems. Biomedical images and videos are ubiquitous and overwhelming in volume, amounting to a database that can be measured in zettabytes.With increased access to open image and video datasets and the recent development of effective image and video analysis systems, there is a unique opportunity for the development of artificial intelligence (AI) systems that can be trained and tested on large-scale biomedical image and video databases. The special issue summarizes emerging methods associated with the development of computer-aided diagnostic systems. More specifically, the special issue discusses the development of methods for dealing with small or large or creating new datasets, biomedical image segmentation, and image classification. The development of new dataset methods allows us to develop methods for specific diseases, employ meta-learning for training on small datasets, or develop methods for reducing larger video datasets. Biomedical image segmentation is a primary focus of the special issue.This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy