SuperPoint features in endoscopy

Conference paper

Leon Barbed, O., Chadebecq, F., Morlana, J., Montiel, J. and Murillo, A. 2022. SuperPoint features in endoscopy. Manfredi, L., Ahmadi, S., Bronstein, M., Kazi, A., Lomanto, D., Mathew, A., Magerand, L., Mullakaeva, K., Papiez, B., Taylor, R. and Trucco, E. (ed.) 1st MICCAI Workshop on Imaging Systems for GI Endoscopy. Singapore 18 - 18 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-21083-9_5
TypeConference paper
TitleSuperPoint features in endoscopy
AuthorsLeon Barbed, O., Chadebecq, F., Morlana, J., Montiel, J. and Murillo, A.
Abstract

There is often a significant gap between research results and applicability in routine medical practice. This work studies the performance of well-known local features on a medical dataset captured during routine colonoscopy procedures. Local feature extraction and matching is a key step for many computer vision applications, specially regarding 3D modelling. In the medical domain, handcrafted local features such as SIFT, with public pipelines such as COLMAP, are still a predominant tool for this kind of tasks. We explore the potential of the well known self-supervised approach SuperPoint [4], present an adapted variation for the endoscopic domain and propose a challenging evaluation framework. SuperPoint based models achieve significantly higher matching quality than commonly used local features in this domain. Our adapted model avoids features within specularity regions, a frequent and problematic artifact in endoscopic images, with consequent benefits for matching and reconstruction results. Training code and models available https://github.com/LeonBP/SuperPointEndoscopy.

KeywordsDeep learning; Self-supervision; Local features; Endoscopy
Sustainable Development Goals3 Good health and well-being
Middlesex University ThemeHealth & Wellbeing
Conference 1st MICCAI Workshop on Imaging Systems for GI Endoscopy
Proceedings TitleImaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis First MICCAI Workshop, ISGIE 2022, and Fourth MICCAI Workshop, GRAIL 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
SeriesLecture Notes in Computer Science
EditorsManfredi, L., Ahmadi, S., Bronstein, M., Kazi, A., Lomanto, D., Mathew, A., Magerand, L., Mullakaeva, K., Papiez, B., Taylor, R. and Trucco, E.
ISSN0302-9743
Electronic1611-3349
ISBN
Paperback9783031210822
Electronic9783031210839
PublisherSpringer
Place of publicationCham
Publication dates
Online09 Dec 2022
Print10 Dec 2022
Publication process dates
Accepted2022
Deposited12 Feb 2024
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-21083-9_5. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-ma...

Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-21083-9_5
Web of Science identifierWOS:000925204900005
LanguageEnglish
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