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