Paper Info
Title
Tissue thickness estimation for high precision head-tracking using a galvanometric laser scanner - a case study.
Abstract
Marker-less optical head-tracking constitutes a comfortable alternative with no exposure to radiation for realtime monitoring in radiation therapy. Supporting information such as tissue thickness has the potential to improve spatial tracking accuracy. Here we study how accurate tissue thickness can be estimated from the near-infrared (NIR) backscatter obtained from laser scans. In a case study, optical data was recorded with a galvanometric laser scanner from three subjects. A tissue ground truth from MRI was robustly matched via customized bite blocks. We show that Gaussian Processes accurately model the relationship between NIR features and tissue thickness. They were able to predict the tissue thickness with less than 0.5 mm root mean square error. Individual scaling factors for all features and an additional incident angle feature had positive effects on this performance.
Year
DOI
Venue
2014
10.1109/EMBC.2014.6944280
EMBC
Keywords
Field
DocType
radiation therapy,high-precision head-tracking,gaussian processes,optical data,tissue thickness estimation,mri,patient monitoring,thickness measurement,marker-less optical head-tracking,optical tracking,galvanometric laser scanner,biomedical mri,spatial tracking accuracy,nir features,feature extraction,root mean square error,incident angle feature,laser applications in medicine,biological tissues,near-infrared backscatter,medical image processing,real-time monitoring
Computer vision,Laser scanning,Computer science,Optics,Head tracking,Artificial intelligence
Conference
Volume
ISSN
Citations 
2014
1557-170X
3
PageRank 
References 
Authors
0.66
3
7
Name
Order
Citations
PageRank
Tobias Wissel1166.16
Patrick Stuber262.42
Benjamin Wagner3387.02
Robert Dürichen4184.32
Ralf Bruder5249.88
Achim Schweikard661.99
Floris Ernst76919.42