The Publication Database hosted by SPL
|
All Publications
Upload
Advanced Search
Gallery View
Download Statistics
Help
Import
Log in
Validation of a Non-Rigid Registration Framework that Accommodates Tissue Resection
|
|
Institution: |
1Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 2Center of Mathematics for Applications, University of Oslo, Norway |
Publication Date: |
Feb-2010 |
Citation: |
SPIE Medical Imaging 2010;7623:762319. |
Presented at: |
SPIE Medical Imaging |
Links: |
http://www.spl.harvard.edu/publications/item/view/1916 |
Appears in Collections: |
NAC, NCIGT, SPL |
Sponsors: |
NIH U41 RR019703 NIH P41 RR13218 |
Generated Citation: |
Risholm P., Samset E., Wells III W.M. Validation of a Non-Rigid Registration Framework that Accommodates Tissue Resection. SPIE Medical Imaging 2010;7623:762319. |
| Downloaded: | 702 times. [view map] |
| Paper: | Download, View online |
| Export citation: |
We present a 3D extension and validation of an intra-operative registration framework that accommodates tissue resection. The framework is based on the bijective Demons method, but instead of regularizing with the traditional Gaussian smoother, we apply an anisotropic diffusion filter with the resection modeled as a diffusion sink. The diffusion sink prevents unwanted Demon forces that originates from the resected area from diffusing into the surrounding area. Another attractive property of the diffusion sink is the resulting continuous deformation field across the diffusion sink boundary, which allows us to move the boundary of the diffusion sink without changing values in the deformation field. The area of resection is estimated by a level-set method evolving in the space of image intensity disagreements in the intra-operative image domain. A product of using the bijective Demons method is that we can also provide an accurate estimate of the resected tissue in the pre- operative image space. Validation of the proposed method was performed on a set of 25 synthetic images. Our experiments show a significant improvement in accommodating resection using the proposed method compared to two other Demons based methods.
Additional Material
1 File (78.408kB)
Risholm-SPIEMI2010-fig2.jpg (78.408kB)