Authors
Hans C Van Assen, Mikhail G Danilouchkine, Alejandro F Frangi, Sebastián Ordás, Jos JM Westenberg, Johan HC Reiber, Boudewijn PF Lelieveldt
Publication date
2006/4/1
Journal
Medical image analysis
Volume
10
Issue
2
Pages
286-303
Publisher
Elsevier
Description
A new technique (SPASM) based on a 3D-ASM is presented for automatic segmentation of cardiac MRI image data sets consisting of multiple planes with arbitrary orientations, and with large undersampled regions. Model landmark positions are updated in a two-stage iterative process. First, landmark positions close to intersections with images are updated. Second, the update information is propagated to the regions without image information, such that new locations for the whole set of the model landmarks are obtained. Feature point detection is performed by a fuzzy inference system, based on fuzzy C-means clustering. Model parameters were optimized on a computer cluster and the computational load distributed by grid computing. SPASM was applied to image data sets with an increasing sparsity (from 2 to 11 slices) comprising images with different orientations and stemming from different MRI acquisition …
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Scholar articles
HC Van Assen, MG Danilouchkine, AF Frangi, S Ordás… - Medical image analysis, 2006