TY - GEN
T1 - Automatic event detection within thrombus formation based on integer programming
AU - Peter, Loic
AU - Pauly, Olivier
AU - Jansen, Sjoert B.G.
AU - Smethurst, Peter A.
AU - Ouwehand, Willem H.
AU - Navab, Nassir
PY - 2013
Y1 - 2013
N2 - After a blood vessel injury, blood platelets progressively aggregate on the damaged site to stop the resulting blood loss. This natural mechanism called thrombosis can however be prone to malfunctions and lead to the complete obstruction of the blood vessel. Thrombosis disorders play a crucial role in coronary artery diseases and the identification of genetic risk predispositions would therefore considerably help their diagnosis and therapy. In vitro experiments are conducted in this purpose by perfusing blood from several donors over a surface of collagen fibres, which results in the progressive attachment of platelets. Based on the segmentation over time of these aggregates called thrombi, we propose in this paper an automatic method combining tracking and event detection which allows the extraction of characteristics of interest for each thrombus growth individually, in order to find a potential correlation between these growth features and blood donors genetic disorders. We demonstrate the benefits of our approach and the accuracy of its results through an experimental validation.
AB - After a blood vessel injury, blood platelets progressively aggregate on the damaged site to stop the resulting blood loss. This natural mechanism called thrombosis can however be prone to malfunctions and lead to the complete obstruction of the blood vessel. Thrombosis disorders play a crucial role in coronary artery diseases and the identification of genetic risk predispositions would therefore considerably help their diagnosis and therapy. In vitro experiments are conducted in this purpose by perfusing blood from several donors over a surface of collagen fibres, which results in the progressive attachment of platelets. Based on the segmentation over time of these aggregates called thrombi, we propose in this paper an automatic method combining tracking and event detection which allows the extraction of characteristics of interest for each thrombus growth individually, in order to find a potential correlation between these growth features and blood donors genetic disorders. We demonstrate the benefits of our approach and the accuracy of its results through an experimental validation.
KW - Microscopy image analysis
KW - event detection
KW - multi-target tracking
KW - thrombus segmentation
UR - http://www.scopus.com/inward/record.url?scp=84875131893&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-36620-8_21
DO - 10.1007/978-3-642-36620-8_21
M3 - Conference contribution
AN - SCOPUS:84875131893
SN - 9783642366192
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 215
EP - 224
BT - Medical Computer Vision
T2 - 2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
Y2 - 5 October 2012 through 5 October 2012
ER -