TY - GEN
T1 - Right ventricular endocardial segmentation in CMR images using a novel inter-modality statistical shape modelling approach
AU - Piazzese, Concetta
AU - Carminati, M. Chiara
AU - Krause, Rolf
AU - Auricchio, Angelo
AU - Weinert, Lynn
AU - Tamborini, Gloria
AU - Pepi, Mauro
AU - Lang, Roberto M.
AU - Caiani, Enrico G.
N1 - Publisher Copyright:
© 2016 CCAL.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - Statistical shape modelling (SSM) approaches have been proposed as a powerful tool to segment the left ventricle in cardiac magnetic resonance (CMR) images. Our aim was to extend this method to segment the RV cavity in CMR images and validate it compared to the conventional gold-standard (GS) manual tracing. A SSM of the RV was built using a database of 4347 intrinsically 3D surfaces, extracted from transthoracic 3D echo cardiographic (3DE) images of 219 retrospective patients. The SSM was then scaled and deformed on the base of some features extracted, with different strategies, from each short-axis plane until a stable condition was reached. The proposed approach, tested on 14 patients, resulted in a high correlation (r2=0.97) and narrow limits of agreement (± 17% error) when comparing the semiautomatic volumes to the GS, confirming the accuracy of this approach in segmenting the RV endocardium.
AB - Statistical shape modelling (SSM) approaches have been proposed as a powerful tool to segment the left ventricle in cardiac magnetic resonance (CMR) images. Our aim was to extend this method to segment the RV cavity in CMR images and validate it compared to the conventional gold-standard (GS) manual tracing. A SSM of the RV was built using a database of 4347 intrinsically 3D surfaces, extracted from transthoracic 3D echo cardiographic (3DE) images of 219 retrospective patients. The SSM was then scaled and deformed on the base of some features extracted, with different strategies, from each short-axis plane until a stable condition was reached. The proposed approach, tested on 14 patients, resulted in a high correlation (r2=0.97) and narrow limits of agreement (± 17% error) when comparing the semiautomatic volumes to the GS, confirming the accuracy of this approach in segmenting the RV endocardium.
UR - http://www.scopus.com/inward/record.url?scp=85016131728&partnerID=8YFLogxK
U2 - 10.22489/cinc.2016.026-356
DO - 10.22489/cinc.2016.026-356
M3 - Conference contribution
AN - SCOPUS:85016131728
T3 - Computing in Cardiology
SP - 1
EP - 4
BT - Computing in Cardiology Conference, CinC 2016
A2 - Murray, Alan
PB - IEEE Computer Society
T2 - 43rd Computing in Cardiology Conference, CinC 2016
Y2 - 11 September 2016 through 14 September 2016
ER -