Abstract：
:In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Duchateau N,De Craene M,Piella G,Silva E,Doltra A,Sitges M,Bijnens BH,Frangi AFdoi
10.1016/j.media.2010.12.006subject
Has Abstractpub_date
2011-06-01 00:00:00pages
316-28issue
3eissn
1361-8415issn
1361-8423pii
S1361-8415(10)00136-2journal_volume
15pub_type
杂志文章abstract：:Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the l...
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journal_title：Medical image analysis
pub_type： 杂志文章,评审
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journal_title：Medical image analysis
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journal_title：Medical image analysis
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journal_title：Medical image analysis
pub_type： 杂志文章,评审
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journal_title：Medical image analysis
pub_type： 杂志文章
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journal_title：Medical image analysis
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