Abstract Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …

This article establishes a comprehensive review of all the different methods proposed by the
literature concerning augmented reality in intra-abdominal minimally invasive surgery (also …

The lack of publicly available ground-truth data has been identified as the major challenge
for transferring recent developments in deep learning to the biomedical imaging domain …

Background Crowdsourcing is a nascent phenomenon that has grown exponentially since it
was coined in 2006. It involves a large group of people solving a problem or completing a …

Background Crowdsourcing involves obtaining ideas, needed services, or content by
soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks …

The number of biomedical image analysis challenges organized per year is steadily
increasing. These international competitions have the purpose of benchmarking algorithms …

We propose a new method that employs transfer learning techniques to effectively correct
sampling selection errors introduced by sparse annotations during supervised learning for …

Abstract Machine learning algorithms are gaining increasing interest in the context of
computer-assisted interventions. One of the bottlenecks so far, however, has been the …

Background Surgery generates a vast amount of data from each procedure. Particularly
video data provides significant value for surgical research, clinical outcome assessment …

Content-based multimedia retrieval (CBMR) has been an active research domain since the
mid 1990s. In medicine visual retrieval started later and has mostly remained a research …