Automatic segmentation of cardiac MRI cines validated for long axis views

Yossi Tsadok; Yael Petrank; Sebastian Sarvari; Thor Edvardsen; Dan Adam

doi:10.1016/j.compmedimag.2013.09.002

Automatic segmentation of cardiac MRI cines validated for long axis views

Comput Med Imaging Graph. 2013 Oct-Dec;37(7-8):500-11. doi: 10.1016/j.compmedimag.2013.09.002. Epub 2013 Sep 12.

Authors

Yossi Tsadok¹, Yael Petrank, Sebastian Sarvari, Thor Edvardsen, Dan Adam

Affiliation

¹ Faculty of Biomedical Engineering, Technion-IIT Technion City, Haifa 32000, Israel. Electronic address: [email protected].

PMID: 24094590
DOI: 10.1016/j.compmedimag.2013.09.002

Abstract

Segmentation of cardiac magnetic resonance imaging is considered an important application in clinical practice. An automatic algorithm is proposed for segmentation of both endocardial and epicardial boundaries, in long-axis views. The data consisted of 126 patients, yielding 1008 traces. Estimated clinical parameters were highly correlated to gold standard measurements. The error between the automatic tracing and the gold standard was not significantly different than the error between two manual observers. In conclusion, a tool for segmenting the myocardial boundaries in the long-axis views is proposed, which works well, as demonstrated by the validation performed using a clinical dataset.

Keywords: Cardiac magnetic resonance imaging (cMRI); Image registration; Image segmentation; Long-axis views; Myocardial segmentation.

Publication types

Evaluation Study
Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Algorithms*
Artificial Intelligence
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging, Cine / methods*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique*
Ventricular Dysfunction, Left / pathology*