ArticleInternational journal of computer assisted radiology and surgery2015
Robust surface tracking combining features, intensity and illumination compensation.
Article in International journal of computer assisted radiology and surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Surgical spectral imaging.Medical image analysis · 2020Review
- HKSiamFC: Visual-Tracking Framework Using Prior Information Provided by Staple and Kalman Filter.Sensors (Basel, Switzerland) · 2020Article
- Use of biomedical photonics in gynecological surgery: a uterine transplantation model.Future science OA · 2018Article
- Real-time geometry-aware augmented reality in minimally invasive surgery.Healthcare technology letters · 2017Article
- Soft tissue motion tracking with application to tablet-based incision planning in laser surgery.International journal of computer assisted radiology and surgery · 2016Article
- Intraoperative measurement of bowel oxygen saturation using a multispectral imaging laparoscope.Biomedical optics express · 2015Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeRecovering tissue deformation during robotic-assisted minimally invasive surgery procedures is important for providing intra-operative guidance, enabling in vivo imaging modalities and enhanced robotic control. The tissue motion can also be used to apply motion stabilization and to prescribe dynamic constraints for avoiding critical anatomical structures.
methodsImage-based methods based independently on salient features or on image intensity have limitations when dealing with homogeneous soft tissues or complex reflectance. In this paper, we use a triangular geometric mesh model in order to combine the advantages of both feature and intensity information and track the tissue surface reliably and robustly.
resultsSynthetic and in vivo experiments are performed to provide quantitative analysis of the tracking accuracy of our method, and we also show exemplar results for registering multispectral images where there is only a weak image signal.
conclusionCompared to traditional methods, our hybrid tracking method is more robust and has improved convergence in the presence of larger displacements, tissue dynamics and illumination changes.
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Registered trials
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