Document Detail

Group-wise registration of point sets for statistical shape models.
MedLine Citation:
PMID:  22692899     Owner:  NLM     Status:  Publisher    
This paper presents a novel, fast, group-wise registration technique based on establishing soft correspondences between groups of point sets. The registration approach is used to create a statistical shape model, capable of learning the shape variations within a training set. The shape model consists of a mean shape and its transformations to all training shapes. We decouple the procedure into two steps: updating the mean shape and registering it to the training shapes. The algorithm alternates between these two steps until convergence. Following the generation of the statistical shape model, we use the soft correspondence approach to register the model to a new observation. We perform extensive experiments on two data sets: lumbar spine and hippocampi. We compare our algorithm to available stateof- the-art group-wise registration algorithms including featurebased and volume-based approaches. We demonstrate improved generalization, specificity and compactness compared to these algorithms.
A Rasoulian; R Rohling; P Abolmaesumi
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-6-05
Journal Detail:
Title:  IEEE transactions on medical imaging     Volume:  -     ISSN:  1558-254X     ISO Abbreviation:  IEEE Trans Med Imaging     Publication Date:  2012 Jun 
Date Detail:
Created Date:  2012-6-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8310780     Medline TA:  IEEE Trans Med Imaging     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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