Imperial College London


Faculty of EngineeringDepartment of Computing

Head of Department of Computing



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BibTex format

author = {Bai, W and Oktay, O and Rueckert, D},
doi = {10.1007/978-3-319-28712-6_15},
pages = {140--145},
publisher = {Springer},
title = {Classification of myocardial infarcted patients by combining shape and motion features},
url = {},
year = {2016}

RIS format (EndNote, RefMan)

AB - Myocardial infarction changes both the shape and motion of the heart. In this work, cardiac shape and motion features are extracted from shape models at ED and ES phases and combined to train a SVM classifier between myocardial infarcted cases and asymptomatic cases. Shape features are characterised by PCA coefficients of a shape model, whereas motion features include wall thickening and wall motion. Evaluated on the STACOM 2015 challenge dataset, the proposed method achieves a high accuracy of 97.5% for classification, which shows that shape and motion features can be useful biomarkers for myocardial infarction, which provide complementary information to late-gadolinium MR assessment.
AU - Bai,W
AU - Oktay,O
AU - Rueckert,D
DO - 10.1007/978-3-319-28712-6_15
EP - 145
PB - Springer
PY - 2016///
SN - 0302-9743
SP - 140
TI - Classification of myocardial infarcted patients by combining shape and motion features
UR -
ER -