A new approach to texture characterization from dynamic CT scans of the liver is presented. Images with the same slice position and corresponding to three typical acquisition phases are analyzed simultaneously. Thereby texture evolution during the propagation of contrast product is taken into account. The method is applied to recognizing hepatie primary tumors. Experiments with various sets of texture parameters and two classification methods show that simultaneous analysis of texture parameters derived from three subsequent acquisition moments improves the classification accuracy.