A marginalized MAP approach and EM optimization for pair-wise registration
| Autor: | William M. Wells, Samson J. Timoner, Mark Jenkinson, Lilla Zöllei |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2007 |
| Předmět: |
Mathematical optimization
Joint entropy Sensitivity and Specificity Dirichlet distribution Article Pattern Recognition Automated symbols.namesake Imaging Three-Dimensional Artificial Intelligence Prior probability Image Interpretation Computer-Assisted Maximum a posteriori estimation Entropy (information theory) Humans Mathematics Likelihood Functions Brain Reproducibility of Results Image Enhancement Magnetic Resonance Imaging Pair wise Subtraction Technique symbols Multinomial distribution Minification Algorithms |
| Zdroj: | Scopus-Elsevier Lecture Notes in Computer Science ISBN: 9783540732723 IPMI |
| Popis: | We formalize the pair-wise registration problem in a maximum a posteriori (MAP) framework that employs a multinomial model of joint intensities with parameters for which we only have a prior distribution. To obtain an MAP estimate of the aligning transformation alone, we treat the multinomial parameters as nuisance parameters, and marginalize them out. If the prior on those is uninformative, the marginalization leads to registration by minimization of joint entropy. With an informative prior, the marginalization leads to minimization of the entropy of the data pooled with pseudo observations from the prior. In addition, we show that the marginalized objective function can be optimized by the Expectation-Maximization (EM) algorithm, which yields a simple and effective iteration for solving entropy-based registration problems. Experimentally, we demonstrate the effectiveness of the resulting EM iteration for rapidly solving a challenging intra-operative registration problem. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|