LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes

Alt B, Kunz C, Katic D, Younis R, Jaekel R, Mueller-Stich BP, Wagner M, Mathis-Ullrich F (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

IEEE/RSJ International Conference on Intelligent Robots and Systems IEEE

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2022-October

Pages Range: 5265-5270

Conference Proceedings Title: IEEE International Conference on Intelligent Robots and Systems

Event location: Kyoto, JPN

ISBN: 9781665479271

DOI: 10.1109/IROS47612.2022.9981178

Abstract

The semantic segmentation of surgical scenes is a prerequisite for task automation in robot assisted interventions. We propose LapSeg3D, a novel DNN-based approach for the voxel-wise annotation of point clouds representing surgical scenes. As the manual annotation of training data is highly time consuming, we introduce a semi-autonomous clustering-based pipeline for the annotation of the gallbladder, which is used to generate segmented labels for the DNN. When evaluated against manually annotated data, LapSeg3D achieves an F1 score of 0.94 for gallbladder segmentation on various datasets of ex-vivo porcine livers. We show LapSeg3D to generalize accurately across different gallbladders and datasets recorded with different RGB-D camera systems.

Authors with CRIS profile

Franziska Mathis-Ullrich

Involved external institutions

ArtiMinds Robotics GmbH DE Germany (DE) Karlsruhe Institute of Technology (KIT) DE Germany (DE) Universitätsklinikum Heidelberg DE Germany (DE)

How to cite

APA:

Alt, B., Kunz, C., Katic, D., Younis, R., Jaekel, R., Mueller-Stich, B.P.,... Mathis-Ullrich, F. (2022). LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes. In IEEE International Conference on Intelligent Robots and Systems (pp. 5265-5270). Kyoto, JPN: Institute of Electrical and Electronics Engineers Inc..

MLA:

Alt, Benjamin, et al. "LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes." Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022, Kyoto, JPN Institute of Electrical and Electronics Engineers Inc., 2022. 5265-5270.

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