Augmentation of Virtual Endoscopic Images with Intra-operative Data using Content-Nets
Esteban Lansaque, A.; Sanchez Ramos, C.; Borras, A.; Gil Resina, D.
Show 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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