PT Unknown
AU Francesco Ciompi
   Oriol Pujol
   O. Rodriguez-Leor
   Carlo Gatta
   Angel Serrano
   Petia Radeva
TI Enhancing In-Vitro IVUS Data for Tissue Characterization
BT 4th Iberian Conference on Pattern Recognition and Image Analysis
PY 2009
BP 241–248
VL 5524
DI 10.1007/978-3-642-02172-5_32
AB Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%.
ER