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Probabilistic Non-rigid Registration of Prostate Images: Modeling and Quantifying Uncertainty
Institution: |
Brigham and Women's Hospital, Harvard Medical School, Boston, USA. |
Publication Date: |
Jun-2011 |
Journal: |
Proc IEEE Int Symp Biomed Imaging |
Volume Number: |
2011 |
Pages: |
553-556 |
Citation: |
Proc IEEE Int Symp Biomed Imaging. 2011 Jun 9;2011:553-556. |
PubMed ID: |
22288004 |
Appears in Collections: |
SPL, NCIGT |
Sponsors: |
P41 RR019703-08 () funded by NCRR NIH HHS R01 CA111288-07 () funded by NCI NIH HHS R01 CA138419-04 () funded by NCI NIH HHS |
Generated Citation: |
Risholm P., Fedorov A., Pursley J., Tuncali K., Cormack R., Wells III W.M. Probabilistic Non-rigid Registration of Prostate Images: Modeling and Quantifying Uncertainty. Proc IEEE Int Symp Biomed Imaging. 2011 Jun 9;2011:553-556. PMID: 22288004. |
| Export citation: |
Registration of pre- to intra-procedural prostate images needs to handle the large changes in position and shape of the prostate caused by varying rectal filling and patient positioning. We describe a probabilistic method for non-rigid registration of prostate images which can quantify the most probable deformation as well as the uncertainty of the estimated deformation. The method is based on a biomechanical Finite Element model which treats the prostate as an elastic material. We use a Markov Chain Monte Carlo sampler to draw deformation configurations from the posterior distribution. In practice, we simultaneously estimate the boundary conditions (surface displacements) and the internal deformations of our biomechanical model. The proposed method was validated on a clinical MRI dataset with registration results comparable to previously published methods, but with the added benefit of also providing uncertainty estimates which may be important to take into account during prostate biopsy and brachytherapy procedures.