Zusammenfassung
Image based documentation of diagnostic findings in screening colonoscopy is currently achieved by capturing single images. Nevertheless, these lack precise information about their location in the colon. Creating a panorama map of the lumen of the colon during the examination, which shows detected lesion in their context, can support the endoscopist during the documentation process. Moreover, such a panoramic map also provides information about the completeness of an examination. An important step towards such a panoramic model is a robust 3D reconstruction of the colon in a first step. Nevertheless, as colonoscopy provides only monocular image data, 3D reconstruction of the colon is challenging. Therefore, we created a 3D reconstruction pipeline, consisting of a DCNN to estimate the depth for a single video frame and the concatenation and fusion of the depth maps to a 3D model based on feature consensus. As with real colonoscopic data, ground truth information regarding the exact extension and geometry of the colon is not available,we produced a modular 3D printed phantom of the colon to evaluate the proposed reconstruction method. The phantom was examined with standard withdrawal motions using two different colonoscopes resulting in endoscopic video streams. From these sequences the3Dreconstruction was computed, and the results were aligned and compared with the ground truth obtained from CAD-blueprint of the phantoms. In all cases, the achieved quality was highly sufficient.
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© 2022 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Hackner, R. et al. (2022). 3D Reconstruction of the Colon from Monocular Sequences Evaluation by 3D-printed Phantom Data. In: Maier-Hein, K., Deserno, T.M., Handels, H., Maier, A., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2022. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-36932-3_31
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DOI: https://doi.org/10.1007/978-3-658-36932-3_31
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