Computer-aided detection of diffuse liver disease in ultrasound images

The authors are developing an automated method of determining measures of texture in liver ultrasound images to improve the accuracy of diagnosis of diffuse liver abnormalities. In each digitized image, the background trend of pixel values is estimated to isolate the underlying pattern of liver texture. After correcting for background trend, the root mean square (RMS) variation and the first moment of the power spectrum are calculated; these measures have been applied successfully to texture analysis of digital chest radiographs. Background trend-corrected measurements detected statistically significant differences in digitized ultrasound images of 11 normal and 11 abnormal livers. Without correction for background trend, the measures are unable to distinguish normal from abnormal liver texture. The authors also investigated the effect on the texture measures of varying several ultrasound imaging parameters in normal patients and in an ultrasound phantom.