TY - GEN
T1 - Cardiac medial modeling and time-course heart wall thickness analysis
AU - Sun, Hui
AU - Avants, Brian B.
AU - Frangi, Alejandro F.
AU - Sukno, Federico
AU - Gee, James C.
AU - Yushkevich, Paul A.
PY - 2008
Y1 - 2008
N2 - The medial model is a powerful shape representation method that models a 3D object by explicitly defining its skeleton (medial axis) and deriving the boundary geometry according to medial geometry. It has been recently extended to model complex shapes with multi-figures, i.e., shapes whose skeletons can not be described by a single sheet in 3D. This paper applied the medial model to a 2-chamber heart data set consisting of 428 cardiac shapes from 90 subjects. The results show that the medial model can capture the heart shape accurately. To demonstrate the usage of the medial model, the changes of the heart wall thickness over time are analyzed. We calculated the mean heart wall thickness map of 90 subjects for different phases of the cardiac cycle, as well as the mean thickness change between phases.
AB - The medial model is a powerful shape representation method that models a 3D object by explicitly defining its skeleton (medial axis) and deriving the boundary geometry according to medial geometry. It has been recently extended to model complex shapes with multi-figures, i.e., shapes whose skeletons can not be described by a single sheet in 3D. This paper applied the medial model to a 2-chamber heart data set consisting of 428 cardiac shapes from 90 subjects. The results show that the medial model can capture the heart shape accurately. To demonstrate the usage of the medial model, the changes of the heart wall thickness over time are analyzed. We calculated the mean heart wall thickness map of 90 subjects for different phases of the cardiac cycle, as well as the mean thickness change between phases.
UR - http://www.scopus.com/inward/record.url?scp=79551683880&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85990-1_92
DO - 10.1007/978-3-540-85990-1_92
M3 - Conference contribution
C2 - 18982674
AN - SCOPUS:79551683880
SN - 3540859896
SN - 9783540859895
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 766
EP - 773
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 - 11th International Conference, Proceedings
PB - Springer-Verlag Italia
T2 - 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008
Y2 - 6 September 2008 through 10 September 2008
ER -