Automatic Detection of Left Ventricular Contours from Cardiac Cine Magnetic Resonance Imaging Using Fuzzy Logic

Abstract

The ejection fraction can be obtained using this automatic contouring method.

Unsupervised Fully Automated Inline Analysis of Global Left Ventricular Function in CINE MR Imaging

“…The different methods include data driven algorithms (edge detection, region growing) and model driven (model fitting) techniques. 19,21,24,25 Unfortunately, most of these algorithms were either insufficiently robust for clinical routine or still time-consuming because of the need for additional segmentation. 26,27 Furthermore, all of these methods were user-dependent, as they relied on manual corrections with associated issues of reproducibility.…”

Evaluation of a New Method for Automated Detection of Left Ventricular Boundaries in Time Series of Magnetic Resonance Images Using an Active Appearance Motion Model

“…Because the contour detection is based on the minimization of the gray value difference between the actual image data of a whole time series of images and the deformed representation of the AAMM, the method is relatively insensitive to false edges present in the images. This is in contrast to other contour detection approaches, which rely on local image features such as gray value edges (Baldy et al, 1994;Lalande et al, 1999;van der Geest et al, 1997). An additional advantage of the presented automated method is that it exploits all image information contained in a time-series of images during detection of the contours.…”

Single and Biplane TrueFISP Cardiovascular Magnetic Resonance for Rapid Evaluation of Left Ventricular Volumes and Ejection Fraction

“…Manual correction of automatically detected contours often takes as long as drawing the contours manually in the first place. It should also be borne in mind that automated contouring is currently unable to exclude the papillary muscles from the volumes (Baldy et al, 1994;Lalande et al, 1999;Plein et al, 2001b).…”