Details
| Original language | English |
|---|---|
| Pages (from-to) | 171-181 |
| Number of pages | 11 |
| Journal | International journal of computer assisted radiology and surgery |
| Volume | 10 |
| Issue number | 2 |
| Publication status | Published - Feb 2015 |
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.
Keywords
- Er:YAG laser surgery, Laser focus adjustment, Surface reconstruction, Tissue ablation
ASJC Scopus subject areas
- Medicine(all)
- Surgery
- Engineering(all)
- Biomedical Engineering
- Medicine(all)
- Radiology Nuclear Medicine and imaging
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Medicine(all)
- Health Informatics
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
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In: International journal of computer assisted radiology and surgery, Vol. 10, No. 2, 02.2015, p. 171-181.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Tissue surface information for intraoperative incision planning and focus adjustment in laser surgery
AU - Schoob, Andreas
AU - Kundrat, Dennis
AU - Kleingrothe, Lukas
AU - Kahrs, Lüder A.
AU - Andreff, Nicolas
AU - Ortmaier, Tobias
N1 - Funding information: The research leading to the presented results has received funding from the European Union Seventh Framework Programme FP7/2007–2013 Challenge 2 Cognitive Systems, Interaction, Robotics under grant agreement RALP - n 288663.
PY - 2015/2
Y1 - 2015/2
N2 - 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.
AB - 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.
KW - Er:YAG laser surgery
KW - Laser focus adjustment
KW - Surface reconstruction
KW - Tissue ablation
UR - http://www.scopus.com/inward/record.url?scp=84938077573&partnerID=8YFLogxK
U2 - 10.1007/s11548-014-1077-x
DO - 10.1007/s11548-014-1077-x
M3 - Article
C2 - 24875655
AN - SCOPUS:84938077573
VL - 10
SP - 171
EP - 181
JO - International journal of computer assisted radiology and surgery
JF - International journal of computer assisted radiology and surgery
SN - 1861-6410
IS - 2
ER -