@InProceedings{FrancescoCiompi2009,
author="Francesco Ciompi
and Oriol Pujol
and O. Rodriguez-Leor
and Carlo Gatta
and Angel Serrano
and Petia Radeva",
title="Enhancing In-Vitro IVUS Data for Tissue Characterization",
booktitle="4th Iberian Conference on Pattern Recognition and Image Analysis",
year="2009",
publisher="Springer Berlin Heidelberg",
volume="5524",
pages="241--248",
abstract="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\%.",
optnote="MILAB;HuPBA",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1162), last updated on Tue, 17 Dec 2013 12:53:06 +0100",
isbn="978-3-642-02171-8",
issn="0302-9743",
doi="10.1007/978-3-642-02172-5_32"
}