%0 Conference Proceedings
%T On in-vitro and in-vivo IVUS data fusion
%A Francesco Ciompi
%A Oriol Pujol
%A O. Rodriguez-Leor
%A Angel Serrano
%A J. Mauri
%A Petia Radeva
%B 12th International Conference of the Catalan Association for Artificial Intelligence
%D 2009
%V 202
%@ 978-1-60750-061-2
%F Francesco Ciompi2009
%O MILAB;HuPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1204), last updated on Tue, 17 Dec 2013 13:22:26 +0100
%X The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data.
%U http://dx.doi.org/10.3233/978-1-60750-061-2-147
%P 147-156