Using radio frequency reconstructed IVUS images in tissue classification

One of the main uses of the Intravascular Ultrasound (IVUS) images is tissue classification. Some of the most important tissues are calcium, fibrotic, and lipid plaque. Usually, this task is achieved using DICOM images. Here we exposed the use of reconstructed images from RF data to improve the classification process, because it is given the advantage of normalizing the images to a fixed parameter set. In this approach, 6 different data sets are generated using 150 tissue sections obtained from 54 images of 6 patients. Then, the images are classified employing adaboost classifiers with Error Correcting Output Codes (ECOC) using 85% of the data for training and the rest for testing. The pixel classification rate for DICOM images is: 76.11% composed of 72% for calcified, 76.13% for fibrotic, and 80.21% for lipid tissue. For reconstructed images the hit rate is 79.03%, from which 77.6% of calcium, 69% of fibrosis and 90.5% of lipid tissue are well detected.