3 papers
cs.CV2023
Domain Adaptation for Medical Image Segmentation using Transformation-Invariant Self-Training
Negin Ghamsarian, Javier Gamazo Tejero, Pablo Márquez Neila +4
Models capable of leveraging unlabelled data are crucial in overcoming large distribution gaps between the acquired datasets across different imaging devices and configurations. In…
cs.CV2023
Full or Weak annotations? An adaptive strategy for budget-constrained annotation campaigns
Javier Gamazo Tejero, Martin S. Zinkernagel, Sebastian Wolf +2
Annotating new datasets for machine learning tasks is tedious, time-consuming, and costly. For segmentation applications, the burden is particularly high as manual delineations of…
eess.IV2021
CataNet: Predicting remaining cataract surgery duration
Andrés Marafioti, Michel Hayoz, Mathias Gallardo +4
Cataract surgery is a sight saving surgery that is performed over 10 million times each year around the world. With such a large demand, the ability to organize surgical wards and…