Document Detail


Improving segmentation of the left ventricle using a two-component statistical model.
MedLine Citation:
PMID:  17354885     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Quality of segmentations obtained by 3D Active Appearance Models (AAMs) crucially depends on underlying training data. MRI heart data, however, often come noisy, incomplete, with respiratory-induced motion, and do not fulfill necessary requirements for building an AAM. Moreover, AAMs are known to fail when attempting to model local variations. Inspired by the recent work on split models we propose an alternative to the methods based on pure 3D AAM segmentation. We interconnect a set of 2D AAMs by a 3D shape model. We show that our approach is able to cope with imperfect data and improves segmentations by 11% on average compared to 3D AAMs.
Authors:
Sebastian Zambal; Jifi Hladůvka; Katja Bühler
Related Documents :
11710765 - Why are arthropods segmented?
1473825 - Analysis of knee vibration signals using linear prediction.
20152685 - Methods for managing 3-dimensional volumes.
19053495 - Texture segmentation by genetic programming.
22835435 - A model for educational simulation of the effect of oxytocin on uterine contractions.
11946365 - An introduction to hybrid computers and their application to optimization problems.
Publication Detail:
Type:  Evaluation Studies; Journal Article    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  9     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2006  
Date Detail:
Created Date:  2007-03-14     Completed Date:  2007-04-06     Revised Date:  2009-12-11    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  151-8     Citation Subset:  IM    
Affiliation:
VRVis Research Center for Virtual Reality and Visualization, Donau-City-Strasse 1, 1220 Vienna, Austria.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Computer Simulation
Heart Ventricles / anatomy & histology*
Humans
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Models, Cardiovascular
Models, Statistical
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Comparing the similarity of statistical shape models using the Bhattacharya metric.
Next Document:  An approach for the automatic cephalometric landmark detection using mathematical morphology and act...