Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

Surgical Planning Laboratory

The Publication Database hosted by SPL

All Publications | Upload | Advanced Search | Gallery View | Download Statistics | Help | Import | Log in

Improving Registration using Multi-channel Diffeomorphic Demons Combined with Certainty Maps

Institution:
1Sectra Imtec, Linkoping, Sweden.
2Department of Biomedical Engineering, Linkoping University, Sweden.
3Center for Medical Image Science and Visualization (CMIV),Linkoping University, Sweden.
4Psychiatry Neuroimaging Laboratory, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.
5Laboratory of Mathematics in Imaging, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.
Publication Date:
Sep-2011
Volume Number:
1
Pages:
19-26
Citation:
Proceedings of the First International Conference on Multimodal Brain Image Analysis 2011 Sep;19-26.
Appears in Collections:
LMI, NAC, PNL, SLICER, SPL
Sponsors:
Swedish Research Council (2007-4786)
AgoraLink at Linkoping University
R01 MH092862/MH/NIMH NIH HHS/United States
R01 MH074794/MH/NIMH NIH HHS/United States
R01 MH082918/MH/NIMH NIH HHS/United States
P41 RR013218/RR/NCRR NIH HHS/United States
Generated Citation:
Forsberg D., Rathi Y., Bouix S., Wassermann D., Knutsson H., Westin C-F. Improving Registration using Multi-channel Diffeomorphic Demons Combined with Certainty Maps. Proceedings of the First International Conference on Multimodal Brain Image Analysis 2011 Sep;19-26.
Downloaded: 894 times. [view map]
Paper: Download, View online
Export citation:
Google Scholar: link

The number of available imaging modalities increases both in clinical practice and in clinical studies. Even though data from multiple modalities might be available, image registration is typically only performed using data from a single modality. In this paper, we propose using certainty maps together with multi-channel diffeomorphic demons in order to improve both accuracy and robustness when performing image registration. The proposed method is evaluated using DTI data, multiple region overlap measures and a fiber bundle similarity metric.

Additional Material
1 File (161.452kB)
Forsberg-MBIA2011-fig1.jpg (161.452kB)