@Inbook{MichalDrozdzal2013,
author="Michal Drozdzal
and Santiago Segui
and Petia Radeva
and Carolina Malagelada
and Fernando Azpiroz
and Jordi Vitria",
chapter="An Application for Efficient Error-Free Labeling of Medical Images",
title="Multimodal Interaction in Image and Video Applications",
year="2013",
publisher="Springer Berlin Heidelberg",
volume="48",
pages="1--16",
abstract="In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of {\textquoteleft}{\textquoteleft}clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert.",
optnote="MILAB; OR;MV",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2235), last updated on Thu, 23 Jan 2014 13:12:54 +0100",
isbn="978-3-642-35931-6",
issn="1868-4394",
doi="10.1007/978-3-642-35932-3_1",
file=":http://refbase.cvc.uab.es/files/DSR2013.pdf:PDF"
}