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A Teuner

Publications and source records attributed to A Teuner.

2 recordsLinked to original sources

[Computer-assisted analysis of ultrasound sequences of the left ventricle for determining ejection fraction].

The present study describes an automatic procedure for calculating the ejection fraction on the basis of ultrasound images. This procedure is divided into three steps, and programmed in C/UNIX. In an initial step, an algorithm, known as sequence analysis, is used to identify the enddiastolic and endsystolic images from a series of ultrasound images. With the use of a template matching procedure for calculating displacement vectors, a method has been developed for the first time for analysing moving images for identification purposes. The subsequent image analysis employs various filter processes for noise suppression, contrast enhancement, image sharpening, edge detection and segmentation. On the basis of the geometrical data of the segmented left ventricle obtained in this way the respective volumes and ejection fraction are calculated. To validate this automatic procedure, the series of ultrasound images were examined by a cardiologist. It was found that the identification of the endsystolic and enddiastolic image was correct, and that there was good agreement between the automatically determined and manually determined ejection fraction.

Algorithms↗

[Algorithm for automatic endocardium identification in digital echocardiography image sequences].

The present paper describes an automated procedure for the detection of left ventricular internal wall edges in digital echocardiographic image sequences. The proposed procedure is divided into three steps and programmed in C/UNIX. It includes the use of a specially designed, application-specific adaptive spatio-temporal filter for noise reduction in echocardiographic image sequences, local 3-D histogram equalization for augmented contrast, and segmentation of the left ventricle using a regional growth method. When designing the adaptive spatio-temporal filter, we took into account the fact that the background noise is correlated in tangential orientation due to beam deflection at interfaces characterized by a large impedance "jump". Using the specially designed filter, the background noise is successfully reduced without degrading the ventricular contours. The simulation results presented highlight the performance of the proposed method in an exemplary manner.

Algorithms↗