Imperial College London


Faculty of EngineeringDepartment of Computing

Head of Department of Computing



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BibTex format

author = {Peressutti, D and Bai, W and Shi, W and Tobon-Gomez, C and Jackson, T and Sohal, M and Rinaldi, A and Rueckert, D and King, A},
doi = {10.1007/978-3-319-28712-6_4},
pages = {30--39},
publisher = {Springer},
title = {Towards left ventricular scar localisation using local motion descriptors},
url = {},
year = {2016}

RIS format (EndNote, RefMan)

AB - We propose a novel technique for the localisation of Left Ventricular (LV) scar based on local motion descriptors. Cardiac MR imaging is employed to construct a spatio-temporal motion atlas where the LV motion of different subjects can be directly compared. Local motion descriptors are derived from the motion atlas and dictionary learning is used for scar classification. Preliminary results on a cohort of 20 patients show a sensitivity and specificity of 80% and 87% in a binary classification setting.
AU - Peressutti,D
AU - Bai,W
AU - Shi,W
AU - Tobon-Gomez,C
AU - Jackson,T
AU - Sohal,M
AU - Rinaldi,A
AU - Rueckert,D
AU - King,A
DO - 10.1007/978-3-319-28712-6_4
EP - 39
PB - Springer
PY - 2016///
SN - 0302-9743
SP - 30
TI - Towards left ventricular scar localisation using local motion descriptors
UR -
ER -