Semiautomatic contour detection in ultrasound M-mode images

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

“…To deal with this problem, many of the methods proposed in the literature have used semi-automatic segmentation (Rabben et al, 2000;Mahdavi et al, 2011;Duarte et al, 2013;Ni et al, 2015), in which a human localizes a suitable region, and then segmentation algorithms delineate the selected region. This study was designed to automatically detect ROIs and delineate their boundaries.…”

Volume Stitching in Three-Dimensional Echocardiography: Distortion Analysis and Extension to Real Time

“…The calculations of S t and T t for a given location were performed in the prolate spheroidal coordinate system: see Rabben et al (2003) for details. The parameter values of these transforms were adapted to a large number of semiautomatically generated contours in M-mode images (Rabben et al 2000). …”

Automated Tracking of the Mitral Valve Annulus Motion in Apical Echocardiographic Images Using Multidimensional Dynamic Programming

“…Common methods for evaluating the mitral annular motion are M-mode echocardiography (Unser et al 1989;Willenheimer et al 1999), two-dimensional (2D) echocardiography (Behar et al 2004;DeCara et al 2005;Eto et al 2005), three-dimensional (3D) echocardiography (Flachskampf et al 2000) and Doppler tissue echocardiography (Rabben et al 2000). Unser et al (1989) performed one-dimensional (1D) dynamic programming (DP) on M-mode echocardiograms for border detection.…”

“…Unser et al (1989) performed one-dimensional (1D) dynamic programming (DP) on M-mode echocardiograms for border detection. Rabben et al (2000) implemented 1D DP on Doppler tissue echocardiograms combined with M-mode grayscale for contour detection. The dominant drawback of M-mode and Doppler tissue echocardiography is that they detect the MVA motion only along a fixed line (angle dependency).…”