Abstract
For endoscopic examinations of the large intestine, the limited field of vision related to the keyhole view of the endoscope can be a problem. A panoramic view of the video images acquired during a colonoscopy can potentially enlarge the field of view in real-time and may ensure that the performing physician has examined the entire organ. To train and test such a panorama-generation system, endoscopic video sequences with information about the geometry are necessary, but rarely exist. Therefore, we created a virtual phantom of the colon with a 3D-modelling software and propose different methods for realistic-looking textures. This allows us to perform a “virtual colonoscopy” and provide a well-defined test environment as well as supplement our training data for deep learning.
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© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Hackner, R., Walluscheck, S., Lehmann, E., Eixelberger, T., Bruns, V., Wittenberg, T. (2021). A Geometric and Textural Model of the Colon as Ground Truth for Deep Learning-based 3D-reconstruction. In: Palm, C., Deserno, T.M., Handels, H., Maier, A., Maier-Hein, K., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2021. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33198-6_73
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DOI: https://doi.org/10.1007/978-3-658-33198-6_73
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