Enhancing virtual bronchoscopy with intra-operative data using a multi-objective GAN
D. Gil Resina, A. Esteban Lansaque, A. Borras, C. Sanchez Ramos
Abstract
State of the art methods in computer vision need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. The particular field of intervention guiding has the extra difficulty of intra-operative recordings probably requiring the alteration of standard protocols.
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