Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery

Autor: Xiaofei Du, Danail Stoyanov, Sebastien Ourselin, Alessio Dore, David J. Hawkes, Maximilian Allan, John D. Kelly
Rok vydání: 2016
Předmět:
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Biomedical Engineering
Health Informatics
02 engineering and technology
Instrument tracking and detection
Tracking (particle physics)
030218 nuclear medicine & medical imaging
Motion
03 medical and health sciences
0302 clinical medicine
Robotic Surgical Procedures
Minimally invasive surgery
3d tracking
0202 electrical engineering
electronic engineering
information engineering
Humans
Minimally Invasive Surgical Procedures
Robot-assisted surgery
Medicine
Radiology
Nuclear Medicine and imaging
Computer vision
ComputingMethodologies_COMPUTERGRAPHICS
business.industry
Surgical vision
General Medicine
Surgical Instruments
Robotic assisted surgery
Computer Graphics and Computer-Aided Design
Computer Science Applications
Surgery
Computer-Assisted
Radiology Nuclear Medicine and imaging
Invasive surgery
Original Article
020201 artificial intelligence & image processing
Surgery
Computer Vision and Pattern Recognition
Artificial intelligence
Fast motion
business
Zdroj: International Journal of Computer Assisted Radiology and Surgery
ISSN: 1861-6429
1861-6410
Popis: Purpose Computer-assisted interventions for enhanced minimally invasive surgery (MIS) require tracking of the surgical instruments. Instrument tracking is a challenging problem in both conventional and robotic-assisted MIS, but vision-based approaches are a promising solution with minimal hardware integration requirements. However, vision-based methods suffer from drift, and in the case of occlusions, shadows and fast motion, they can be subject to complete tracking failure. Methods In this paper, we develop a 2D tracker based on a Generalized Hough Transform using SIFT features which can both handle complex environmental changes and recover from tracking failure. We use this to initialize a 3D tracker at each frame which enables us to recover 3D instrument pose over long sequences and even during occlusions. Results We quantitatively validate our method in 2D and 3D with ex vivo data collected from a DVRK controller as well as providing qualitative validation on robotic-assisted in vivo data. Conclusions We demonstrate from our extended sequences that our method provides drift-free robust and accurate tracking. Our occlusion-based sequences additionally demonstrate that our method can recover from occlusion-based failure. In both cases, we show an improvement over using 3D tracking alone suggesting that combining 2D and 3D tracking is a promising solution to challenges in surgical instrument tracking. Electronic supplementary material The online version of this article (doi:10.1007/s11548-016-1393-4) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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