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BY 4.0 license Open Access Published by De Gruyter November 26, 2020

Deep-learning based reconstruction of the stomach from monoscopic video data

  • Ralf Hackner EMAIL logo , Martin Raithel , Edgar Lehmann and Thomas Wittenberg


For the gastroscopic examination of the stomach, the restricted field of view related to the „keyhole“-perspective of the endoscope is known to be a visual limitation. Thus, a panoramic extension can enlarge the field of vision, supports the endoscopist during the examination, and ensures that all of the inner stomach walls are visually inspected. To compute such a panorama of the stomach, knowledge about the geometry of the underlying structure is required. Structure from motion an approach to reconstruct the necessary information about the 3D-structure from monocular image sequences as provided by a gastroscope. We examine and evaluate an existing deep neuronal network for stereo reconstruction, in order to approximate the geometry of stomach parts from a set of consecutive acquired image pairs from gastroscopic videos.

Published Online: 2020-11-26
Published in Print: 2020-09-01

© 2020 by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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