This paper presents a combination of signal processing and image processing techniques for automatic segmentation and characterization of intravascular ultrasound images. This system is comprised of two modules, the tissue characterization module and the calcium quantification module. The tissue characterization module is based on classification of RF signal performed by a self-organizing map (SOM) previously trained. The calcium quantification module, using the image generated by the envelop of the RF signal, performs an adaptive thresholding based on the Otsu's method. The thresholding process is followed by the analysis of the acoustic shadow regime of the input image which permits to distinguish calcification regions from other small bright regions that, usually, still remain in the image after the thresholding processing.