Characterization of beef muscle tissue using texture analysis of ultrasonic images

Abstract

In the Unites States, commercially available beef is subjectively graded by certified inspectors. The primary factors in determining beef quality grades are the amount and distribution (or marbling) of intramuscular fat. There is a growing demand in the meat industry for an objective system of evaluating the quality of beef carcasses as well as live animals. Ultrasound has been shown to have a good potential for this application. Our approach was to use texture analysis of the ultrasonic images from rib-eye muscle of live animals to evaluate h"uscular fat and marbling. Two approaches of texture analysis, namely spatial gray-level dependence matrices and gray-level run-length matrices, were used. The significant texture parameters were statistically analyzed to derive the models for predicting marbling scores and percentage of fat. The preliminary results showed a good potential of these approaches for tissue characterization and objectively evaluating beef quality.

Adaboost to Classify Plaque Appearance in IVUS Images

“…The unreliability of gray level only methods to achieve good discrimination among the different kind of tissues forced us to use more complex measures, usually based on texture analysis. Several researching groups have reported different approximations to characterize the tissue of intravascular ultrasound images [1] [2] [3]. Most of the literature found in the tissue characterization matters use texture features, being co-occurrence matrices the most popular of all feature extractors.…”