Abstract
We present a method for prediction of atherosclerotic growth based on a training set of 229 2D manually annotated baseline and corresponding follow-up calcifications from lateral X-ray images over an 8 year period. The prediction uses affine shape analysis based on singular value decomposition where non-rigid shapes are modeled as projections of rigid high-dimensional shapes. The SVD prediction was compared to growth based on dilation and predictive conditional PCA. The SVD model yields the largest Jaccard score indicating that the SVD model captures the most of the growth. We also found that small circular shapes grow the most which is likely due to the higher growth potential in smaller calcifications. Furthermore, we are able to predict the biological risk factors better by a joint shape and biology model that suggests a relationship between the shapes and the risk factors.
Original language | English |
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Title of host publication | 2011 IEEE International Symposium on Biomedical Imaging : from nano to macro |
Number of pages | 4 |
Publisher | IEEE |
Publication date | 2011 |
Pages | 1430-1433 |
ISBN (Print) | 978-1-4244-4127-3 |
ISBN (Electronic) | 978-1-4244-4128-0 |
DOIs | |
Publication status | Published - 2011 |
Event | 8th IEEE International Symposium on Biomedical Imaging: from nano to macro - Chicago, United States Duration: 30 Mar 2011 → 2 Apr 2011 Conference number: 8 |
Conference
Conference | 8th IEEE International Symposium on Biomedical Imaging |
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Number | 8 |
Country/Territory | United States |
City | Chicago |
Period | 30/03/2011 → 02/04/2011 |