Tissue surface information for intraoperative incision planning and focus adjustment in laser surgery

verfasst von
Andreas Schoob, Dennis Kundrat, Lukas Kleingrothe, Lüder A. Kahrs, Nicolas Andreff, Tobias Ortmaier
Abstract

Purpose : Introducing computational methods to laser surgery are an emerging field. Focusing on endoscopic laser interventions, a novel approach is presented to enhance intraoperative incision planning and laser focusing by means of tissue surface information obtained by stereoscopic vision.

Methods : Tissue surface is estimated with stereo-based methods using nonparametric image transforms. Subsequently, laser-to-camera registration is obtained by ablating a pattern on tissue substitutes and performing a principle component analysis for precise laser axis estimation. Furthermore, a virtual laser view is computed utilizing trifocal transfer. Depth-based laser focus adaptation is integrated into a custom experimental laser setup in order to achieve optimal ablation morphology. Experimental validation is conducted on tissue substitutes and ex vivo animal tissue.

Results : Laser-to-camera registration gives an error between planning and ablation of less than 0.2 mm. As a result, the laser workspace can accurately be highlighted within the live views and incision planning can directly be performed. Experiments related to laser focus adaptation demonstrate that ablation geometry can be kept almost uniform within a depth range of 7.9 mm, whereas cutting quality significantly decreases when the laser is defocused.

Conclusions : An automatic laser focus adjustment on tissue surfaces based on stereoscopic scene information is feasible and has the potential to become an effective methodology for optimal ablation. Laser-to-camera registration facilitates advanced surgical planning for prospective user interfaces and augmented reality extensions.

Organisationseinheit(en)
Institut für Mechatronische Systeme
Externe Organisation(en)
Universite de Franche-Comte
Typ
Artikel
Journal
International journal of computer assisted radiology and surgery
Band
10
Seiten
171-181
Anzahl der Seiten
11
ISSN
1861-6410
Publikationsdatum
02.2015
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Chirurgie, Biomedizintechnik, Radiologie, Nuklearmedizin und Bildgebung, Maschinelles Sehen und Mustererkennung, Gesundheitsinformatik, Angewandte Informatik, Computergrafik und computergestütztes Design
Elektronische Version(en)
https://doi.org/10.1007/s11548-014-1077-x (Zugang: Geschlossen)