NDLI: Evaluation of different statistical shape models for segmentation of the left ventricular endocardium from magnetic resonance images

Content Provider	IEEE Xplore Digital Library
Author	Piazzese, Concetta Carminati, M. Chiara Colombo, Andrea Krause, Rolf Potse, Mark Weinert, Lynn Tamborini, Gloria Pepi, Mauro Lang, Roberto M. Caiani, Enrico G.
Copyright Year	2015
Description	Author affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy (Piazzese, Concetta; Colombo, Andrea; Caiani, Enrico G.) \|\| Department of Cardiology, University of Chicago, IL, USA (Weinert, Lynn; Lang, Roberto M.) \|\| Centro Cardiologico Monzino IRCCS, Milan, Italy (Carminati, M. Chiara; Tamborini, Gloria; Pepi, Mauro) \|\| Università della Svizzera Italiana, Lugano, Switzerland (Krause, Rolf; Potse, Mark)
Abstract	Statistical shape models (SSMs) represent a powerful tool used in patient-specific modeling to segment medical images because they incorporate a-priori knowledge that guide the model during deformation. Our aim was to evaluate segmentation accuracy in terms of left ventricular (LV) volumes obtained using four different SSMs versus manual gold standard tracing on cardiac magnetic resonance (CMR) images. A database of 3D echocardiographic (3DE) LV surfaces obtained in 435 patients was used to generate four different SSMs, based on cardiac phase selection. Each model was scaled and deformed to detect LV endocardial contours in the end-diastolic (ED) and end-systolic (ES) frames of a CMR short-axis (SAX) stack for 15 patients with normal LV function. Linear correlation and Bland-Altman analyses versus gold-standard showed in all cases high correlation (r2>0.95), non-significant biases and narrow limits of agreement.
Starting Page	105
Ending Page	108
File Size	709131
Page Count	4
File Format	PDF
ISBN	9781509006854
ISSN	2325887X
e-ISBN	9781509006847
DOI	10.1109/CIC.2015.7408597
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-06
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Creative Commons Attribution License 2.5 (CCAL)
Subject Keyword	Image segmentation Three-dimensional displays Biomedical imaging Magnetic resonance imaging Motion segmentation Image edge detection Statistical analysis
Content Type	Text
Resource Type	Article
Subject	Computer Science Cardiology and Cardiovascular Medicine

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