dc.creatorBenjumea, Eberto
dc.creatorSierra, Juan S
dc.creatorMeza, Jhacson
dc.creatorMarrugo, Andres G.
dc.date.accessioned2023-07-21T20:51:05Z
dc.date.accessioned2023-09-06T15:49:37Z
dc.date.available2023-07-21T20:51:05Z
dc.date.available2023-09-06T15:49:37Z
dc.date.created2023-07-21T20:51:05Z
dc.date.issued2022
dc.identifierMarrugo, A. G. (2021, June). Multi-target Attachment for Surgical Instrument Tracking. In Pattern Recognition: 13th Mexican Conference, MCPR 2021, Mexico City, Mexico, June 23–26, 2021, Proceedings (Vol. 12725, p. 345). Springer Nature.
dc.identifierhttps://hdl.handle.net/20.500.12585/12397
dc.identifier10.1007/978-3-030-77004-4_33
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio Universidad Tecnológica de Bolívar
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8683213
dc.description.abstractThe pose estimation of a surgical instrument is a common problem in the new needs of medical science. Many instrument tracking methods use markers with a known geometry that allows for solving the instrument pose as detected by a camera. However, marker occlusion happens, and it hinders correct pose estimation. In this work, we propose an adaptable multi-target attachment with ArUco markers to solve occlusion problems on tracking a medical instrument like an ultrasound probe or a scalpel. Our multi-target system allows for precise and redundant real-time pose estimation implemented in OpenCV. Encouraging results show that the multi-target device may prove useful in the clinical setting. © 2021, Springer Nature Switzerland AG.
dc.languageeng
dc.publisherCartagena de Indias
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleMulti-target Attachment for Surgical Instrument Tracking


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