Biomedical subjects

A Hammoude

Publications and source records attributed to A Hammoude.

3 recordsLinked to original sources

PubMed1999

Edge detection in ultrasound images based on differential tissue attenuation rates.

Identification of the cardiac borders is a basic goal in the analysis of echocardiographic images. This is a requirement for various analysis purposes, such as the derivation of quantitative parameters, for wall motion analysis and for the creation of three-dimensional reconstructions. Border identification is usually accomplished by first identifying a set of generic edge points, then extracting the border of interest from the edge map. A variety of edge detection algorithms have been reported in the literature. However, the most commonly used methods are all based on the same underlying tissue discriminant, namely, the widely differing backscatter levels of the different types of tissue that form the cardiac borders, in particular, blood and myocardium. We have implemented a new method of edge detection based on an entirely different ultrasonic tissue characteristic--that of attenuation, the rate at which the tissue absorbs ultrasonic energy. This characteristic also differs widely between blood and myocardium, and therefore provides an alternative means of discriminating between these two types of tissue. The method searches for the abrupt change in attenuation rate that characteristically occurs at the blood/myocardium interface. At each point in the image, the average attenuation rates of the portions of tissue radially preceding and radially following the point are determined by least-squares regression. If one of these attenuation rates is sufficiently close to that of blood, and the other is sufficiently close to that of myocardium, then the point is flagged as an edge point. This paper describes how this method is implemented in software, and presents the results of applying the method to a library of sample images.

Algorithms↗

PubMedDate not supplied

An empirical parameter selection method for endocardial border identification algorithms.

Identification of the cardiac borders is a basic goal in the analysis of echocardiographic images. For this reason there has been a great deal of interest in automatic border identification methods. Numerous studies have been published, describing a wide variety of proposed methods. In spite of the large number of published studies, however, the relative merits of the various methods remain unclear. Furthermore, the optimal configuration of each method is in most cases unknown. One of the reasons for this is the lack of a well-defined, rigorous method for evaluating and comparing alternative algorithms and/or configurations. In this article we describe a systematic, empirical procedure for evaluating border identification algorithms. The method is based on a strict metrical measure of border error, and a set of test images which reflect the heterogeneity of typical clinical images. The methodology can be used to compare alternative analysis methods, or to determine the optimal configuration for any particular analysis method. We then apply this methodology to the problem of determining parameter values for several of the most commonly used analysis methods.

Algorithms↗

PubMedDate not supplied

Endocardial border identification in two-dimensional echocardiographic images: review of methods.

A basic goal in the analysis of echocardiographic images is to identify the locations of the endocardial borders. This is necessary in order to create three-dimensional reconstructions, and to derive precise quantitative parameters from the images. Endocardial borders can be identified manually; however, this is time-consuming, inconvenient, and liable to human subjectivity. For this reason there has been a great deal of interest in automatic border identification methods. In recent years numerous studies have been published, describing a wide variety of proposed border identification algorithms. In spite of the large number of published studies, however, the relative merits of the various methods remain unclear. In this paper the various analysis techniques are reviewed and discussed. The reasons for the lack of definitive conclusions regarding the utility of these methods are described. Finally, the basic methodological requirements necessary for empirical evaluation of border identification techniques are described.

Algorithms↗