Automatic image-driven segmentation of cardiac ventricles in cine anatomical MRI

Chris A. Cocosco; Wiro J. Niessen; Thomas Netsch; Evert-jan P. A. Vonken; Max A. Viergever

doi:10.1117/12.625575

16 September 2005 Automatic image-driven segmentation of cardiac ventricles in cine anatomical MRI

Chris A. Cocosco, Wiro J. Niessen, Thomas Netsch, Evert-jan P. A. Vonken, Max A. Viergever

Proceedings Volume 5909, Applications of Digital Image Processing XXVIII; 59091M (2005) https://doi.org/10.1117/12.625575
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

The automatic segmentation of the heart's two ventricles from dynamic ("cine") cardiac anatomical images, such as 3D+time short-axis MRI, is of significant clinical importance. Previously published automated methods have various disadvantages for routine clinical use. This work reports about a novel automatic segmentation method that is very fast, and robust against anatomical variability and image contrast variations. The method is mostly image-driven: it fully exploits the information provided by modern 4D (3D+time) balanced Fast Field Echo (bFFE) cardiac anatomical MRI, and makes only few and plausible assumptions about the images and the imaged heart. Specifically, the method does not need any geometrical shape models nor complex gray-level appearance models. The method simply uses the two ventricles' contraction-expansion cycle, as well as the ventricles' spatial coherence along the time dimension. The performance of the cardiac ventricles segmentation method was demonstrated through a qualitative visual validation on 32 clinical exams: no gross failures for the left-ventricle (right-ventricle) on 32 (30) of the exams were found. Also, a clinical validation of resulting quantitative cardiac functional parameters was performed against a manual quantification of 18 exams; the automatically computed Ejection Fraction (EF) correlated well to the manually computed one: linear regression with RMS=3.7% (RMS expressed in EF units).

Citation Download Citation

Chris A. Cocosco, Wiro J. Niessen, Thomas Netsch, Evert-jan P. A. Vonken, and Max A. Viergever "Automatic image-driven segmentation of cardiac ventricles in cine anatomical MRI", Proc. SPIE 5909, Applications of Digital Image Processing XXVIII, 59091M (16 September 2005); https://doi.org/10.1117/12.625575

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