Automatic segmentation and tracking of thrombus formation within in vitro microscopic video sequences

There is a need to more accurately link human genetic variance with thrombotic risk. Thrombus formation results from adhesion of blood platelets to a site of injury, followed by their progressive aggregation and occasional embolization. To observe this in vitro, blood is perfused over a surface of c...

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Bibliographic Details
Published in2012 9th IEEE International Symposium on Biomedical Imaging (ISBI) pp. 1635 - 1638
Main Authors Peter, L., Brieu, N., Jansen, S., Smethurst, P. A., Ouwehand, W. H., Navab, N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Blood
Decision trees
Feature extraction
Image segmentation
In vitro
Merging
Microscopy
Microscopy image analysis
segmentation
supervised classification
thrombus formation
tracking
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Summary:There is a need to more accurately link human genetic variance with thrombotic risk. Thrombus formation results from adhesion of blood platelets to a site of injury, followed by their progressive aggregation and occasional embolization. To observe this in vitro, blood is perfused over a surface of collagen fibres, during video microscopy. This paper proposes three complementary gradient-based features which, if included in a regularized machine learning framework, yield the accurate segmentation of thrombi during such acquisitions. A novel tracking method of thrombi as deformable growing objects under split and merge conditions is also introduced.
ISBN:145771857X
9781457718571
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2012.6235890