In vivo study of on-line liver tissue classification based on envelope power spectrum analysis

An ultrasonic imaging and signal analysis system combining a 3.5-MHz linear array B-scanner and an array processor was realized for a clinical liver tissue classification study. Based on the complete unprocessed RF data set of a real-time B-image, local envelope power spectra averaged over interactively defined regions are computed. These spectra are corrected for tissue-type-independent effects. A library containing the in vivo data of 65 patients with known liver tissue states in three groups (normal, cirrhotic, fat) was built up. An algorithm based on numerical optimization of parameterized spectrum characteristics combined with a k-nearest-neighbors classifier, applied to the library, leads to correct classification rates of 85.8 to 87.5% is discriminating pathological from normal tissue states.<<ETX>>

[1]  C. K. Yuen,et al.  Theory and Application of Digital Signal Processing , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  F. Harris On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[3]  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.

[4]  I. Claesson,et al.  Frequency- and depth-dependent compensation of ultrasonic signals , 1988, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[5]  R. F. Wagner,et al.  Pattern Recognition Methods for Optimizing Multivariate Tissue Signatures in Diagnostic Ultrasound , 1986, Ultrasonic imaging.

[6]  P. M. Gammell,et al.  Improved ultrasonic detection using the analytic signal magnitude , 1981 .