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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Abstract: Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training
verfasst von : Sandy Engelhardt, Lalith Sharan, Matthias Karck, Raffaele De Simone, Ivo Wolf
Erschienen in: Bildverarbeitung für die Medizin 2020
Verlag: Springer Fachmedien Wiesbaden
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Phantoms for surgical training are able to mimic cutting and suturing properties and patient-individual shape of organs, but lack a realistic visual appearance that captures the heterogeneity of surgical scenes. In order to overcome this in endoscopic approaches, hyperrealistic concepts have been proposed to be used in an augmented reality-setting, which are based on deep image-to-image transformation methods. Such concepts are able to generate realistic representations of phantoms learned from real intraoperative endoscopic sequences.