Abstract
Ultrasound images are formed through the interaction between the ultrasonic waves and the body tissue. The propagation of the ultrasound waves through different tissues, their reflection, dispersion, and absorption are primarily determined by the mechanical properties of the tissue. Therefore, the visual representation of the received signal contains the information about the tissue structure and composition, and ultrasound tissue characterization could be a promising new technique for evaluation of patients with coronary artery disease.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aylward PE, McPherson DD, Kerber RE, Skorton D, Collins M. Ultrasonic tissue characterization in coronary artery disease. In: Kerber R, ed. Echochar-diography in Coronary Artery Disease. New York: Futura; 1988:509–531.
Chang T, Kuo C. Texture analysis and classification with tree-structured wavelet transform. IEEE Trans Image Processing. 1993;2:429–441.
Chellappa R. Two dimensional discrete Gaussian Markov random field models for image processing. Pattern Recognition. 1985;2:79–112.
Chen C, Daponte J, Fox M. Fractal feature analysis and classification in medical imaging. IEEE Trans Med Imaging. 1989;6:133–142.
Daubechies I. Ten Lectures on Wavelets. Philadelphia: Society for Industrial and Applied Mathematics; 1992.
Daubechies I. The Wavelet transform, time-frequency localization, and signal analysis. IEEE Trans Inform Theory. 1990;36:961–1005.
Galloway M. Texture analysis using gray level run lengths. Comput Graphics Image Processing. 1975;4:172–199.
Geiser AE. Applications of automatic edge detection and image enhancement techniques to two-dimensional echocardiography and coronary disease. In: Kerber R, ed. Echochardiography in Coronary Artery Disease. New York: Futura; pp. 483–508,1988.
Haralick RM. Statistical and structural approaches to texture. Proc IEEE. 1979;67:786–804.
Havlice J, Taenzer J. Medical ultrasonic imaging: An overview of principles and instrumentation. In: Lee H, Wade G, ed. Modern Acoustical Imaging. New York: IEEE Press; 1986:125–146.
Jain AK, Farrokhia F. Unsupervised texture segmentation using Gabor filters. Pattern Recognition. 1991;24:1167–1186.
Kashyap RL, Chellappa R. Texture synthesis using 2-D noncausal autoregressive models. IEEE Trans Acoustics Speech Signal Processing. 1985;33:194–203.
Laws KI. Textured Image Segmentation. Los Angeles: Image Processing Institvte, University of Southern California; 1980. Thesis.
Mallat S. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans Pattern Anal Machine Intell. 1989;11:674–693.
McPherson DD, Aylward PE, Knosp BM. Ultrasound characterization of acute myocardial ischemia by quantitative texture analysis. Ultrasonic Imaging. 1986; 8:227.
Mojsilović A. Analysis of Ultrasound Images in Cardiology Using Texture Operators. Faculty of Electrical Engineering, Belgrade University, 1994:42–52. Thesis.
MojsiloviĆ A, PopoviĆ A, NeŠkoviĆ A, Amodaj N, PopoviĆ M. Prediction of successful reperfusion after acute myocardial infarction using computer program for myocardial tissue characterization, J Am Coll Cardiol. (special issue) 1995;(Feb.):179A–180A.
MojsiloviĆ A, PopovĆ M, PopoviĆ A, NeŠkoviĆ A, ObradoviĆ V. Analysis and classification of myocardial tissue with the wavelet image extension. Proceedings IEEE International Conference on Image Processing, Vol. 2. Washington DC; 1995:504–507.
Pentland AP. Fractal based description of natural scenes. IEEE Trans Pattern Anal Machine Intell. 1984;6:661–675.
Trivedi MH, Harlow CA, Conners RW, Goh S. Object detection based on gray level cooccurrence. Comput Vision Graphics Image Processing. 1984;28:199–219.
Unser M. Local linear transforms for texture measurements. Signal Processing. 1986;11:61–79.
Unser M, Eden M. Multiresolution feature extraction and selection for texture segmentation. IEEE Trans Pattern Anal Machine Intelligence. 1989;11:717–728.
Weszka JS, Dryer CR, Rosenfeld A. A comparative study of texture measures for terrain classification. IEEE Trans Syst Man Cybern. 1976;6:269–285.
Wu CM, Chen YC, Hsieh KS. Texture features for classification of ultrasonic liver images. IEEE Trans Med Imaging. 1992;11:141–151.
Rights and permissions
Copyright information
© 1998 Springer Science+Business Media New York
About this chapter
Cite this chapter
Mojsilović, A., Nešković, A.N., Popović, M., Popović, A.D. (1998). Computer-Based Myocardial Tissue Characterization Using Quantitative Description of Texture. In: Analysis and Assessment of Cardiovascular Function. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1744-2_6
Download citation
DOI: https://doi.org/10.1007/978-1-4612-1744-2_6
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-7261-8
Online ISBN: 978-1-4612-1744-2
eBook Packages: Springer Book Archive