Autoregressive spectral estimation in ultrasonic scatterer size imaging.

An autoregressive (AR) spectral estimation method was considered for the purpose of estimating scatterer size images. The variance and bias of the resulting estimates were compared with those using classical FFT periodograms for a range of input signal-to-noise ratios and echo-signal durations corresponding to various C-scan image slice thicknesses. The AR approach was found to produce images of significantly higher quality for noisy data and when thin slices were required. Several images reconstructed with the two techniques are presented to demonstrate difference in visual quality. Task-specific guidelines for empirical selection of the AR model order are also proposed.

[1]  R. F. Wagner,et al.  A comparison of autoregressive spectral estimation algorithms and order determination methods in ultrasonic tissue characterization , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[2]  M. Insana,et al.  Modeling acoustic backscatter from kidney microstructure using an anisotropic correlation function. , 1995, The Journal of the Acoustical Society of America.

[3]  T J Hall,et al.  Identifying acoustic scattering sources in normal renal parenchyma in vivo by varying arterial and ureteral pressures. , 1992, Ultrasound in medicine & biology.

[4]  A Fort,et al.  Adaptive SVD-based AR model order determination for time-frequency analysis of Doppler ultrasound signals. , 1995, Ultrasound in medicine & biology.

[5]  T J Hall,et al.  Parametric Ultrasound Imaging from Backscatter Coefficient Measurements: Image Formation and Interpretation , 1990, Ultrasonic imaging.

[6]  E. Feleppa,et al.  Relationship of Ultrasonic Spectral Parameters to Features of Tissue Microstructure , 1987, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[7]  A J Tajik,et al.  Feasibility of identifying amyloid and hypertrophic cardiomyopathy with the use of computerized quantitative texture analysis of clinical echocardiographic data. , 1989, Journal of the American College of Cardiology.

[8]  A Manduca,et al.  Improvement in specificity of ultrasonography for diagnosis of breast tumors by means of artificial intelligence. , 1992, Medical physics.

[9]  R. F. Wagner,et al.  Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[10]  D J Coleman,et al.  Correlations of acoustic tissue typing of malignant melanoma and histopathologic features as a predictor of death. , 1990, American journal of ophthalmology.

[11]  J. G. Miller,et al.  Contraction-related variation in frequency dependence of acoustic properties of canine myocardium. , 1989, The Journal of the Acoustical Society of America.

[12]  R. F. Wagner,et al.  Application of autoregressive spectral analysis to cepstral estimation of mean scatterer spacing , 1993, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[13]  Non-conventional ultrasonography (power spectrum analysis) in the management of retinoblastoma. , 1993, Ophthalmic paediatrics and genetics.

[14]  R. F. Wagner,et al.  High resolution ultrasonic backscatter coefficient estimation based on autoregressive spectral estimation using Burg's algorithm , 1994, IEEE Trans. Medical Imaging.

[15]  D J Coleman,et al.  Ultrasonic tissue characterization and histopathology in tumor xenografts following ultrasonically induced hyperthermia. , 1986, Ultrasound in medicine & biology.

[16]  Brent K. Hoffmeister,et al.  Detection of Unique Transmural Architecture of Human Idiopathic Cardiomyopathy by Ultrasonic Tissue Characterization , 1992, Circulation.

[17]  G G Cox,et al.  Effects of endothelin-1 on renal microvasculature measured using quantitative ultrasound. , 1995, Ultrasound in medicine & biology.

[18]  Application of autoregressive spectral analysis for ultrasound attenuation: interest in highly attenuating medium , 1993 .

[19]  T. Hall,et al.  Renal Ultrasound Using Parametric Imaging Techniques to Detect Changes in Microstructure and Function , 1993, Investigative radiology.