TY  - JOUR
AU  - Sergio Escalera
AU  - Oriol Pujol
AU  - J. Mauri
AU  - Petia Radeva
PY  - 2009//
TI  - Intravascular  Ultrasound Tissue Characterization with Sub-class Error-Correcting  Output Codes
JO  - Journal of Signal Processing Systems
SP  - 35–47
VL  - 55
IS  - 1-3
N2  - Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.
SN  - 1939-8018
UR  - http://dx.doi.org/10.1007/s11265-008-0180-z
N1  - MILAB;HuPBA
ID  - Sergio Escalera2009
ER  -