TY - GEN
T1 - Non-rigid image registration with equally weighted assimilated surface constraint
AU - Zhang, Cheng
AU - Christensen, Gary E.
AU - Murphy, Martin J.
AU - Weiss, Elisabeth
AU - Williamson, Jeffrey F.
PY - 2014
Y1 - 2014
N2 - An important research problem in image-guided radiation therapy is how to accurately register daily onboard Cone-beam CT (CBCT) images to higher quality pretreatment fan-beam CT (FBCT) images. Assuming the organ segmentations are both available on CBCT and FBCT images, methods have been proposed to use them to help the intensity-driven image registration. Due to the low contrast between soft-tissue structures exhibited in CBCT, the interobserver contouring variability (expressed as standard deviation) can be as large as 2-3 mm and varies systematically with organ, and relative location on each organ surface. Therefore the inclusion of the segmentations into registration may degrade registration accuracy. To address this issue we propose a surface assimilation method that estimates a new surface from the manual segmentation from a priori organ shape knowledge and the interobserver segmentation error. Our experiment results show the proposed method improves registration accuracy compared to previous methods.
AB - An important research problem in image-guided radiation therapy is how to accurately register daily onboard Cone-beam CT (CBCT) images to higher quality pretreatment fan-beam CT (FBCT) images. Assuming the organ segmentations are both available on CBCT and FBCT images, methods have been proposed to use them to help the intensity-driven image registration. Due to the low contrast between soft-tissue structures exhibited in CBCT, the interobserver contouring variability (expressed as standard deviation) can be as large as 2-3 mm and varies systematically with organ, and relative location on each organ surface. Therefore the inclusion of the segmentations into registration may degrade registration accuracy. To address this issue we propose a surface assimilation method that estimates a new surface from the manual segmentation from a priori organ shape knowledge and the interobserver segmentation error. Our experiment results show the proposed method improves registration accuracy compared to previous methods.
UR - http://www.scopus.com/inward/record.url?scp=84903751163&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-08554-8_4
DO - 10.1007/978-3-319-08554-8_4
M3 - Conference contribution
AN - SCOPUS:84903751163
SN - 9783319085531
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 31
EP - 40
BT - Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings
PB - Springer Verlag
T2 - 6th International Workshop on Biomedical Image Registration, WBIR 2014
Y2 - 7 July 2014 through 8 July 2014
ER -