@InProceedings{AuraHernandez-Sabate2011,
author="Aura Hernandez-Sabate
and Debora Gil
and David Roche
and Monica M. S. Matsumoto
and Sergio S. Furuie",
editor="Pedro Real
and Daniel Diaz-Pernil
and Helena Molina-Abril
and Ainhoa Berciano
and Walter Kropatsch",
title="Inferring the Performance of Medical Imaging Algorithms",
booktitle="14th International Conference on Computer Analysis of Images and Patterns",
series="L",
year="2011",
publisher="Springer-Verlag Berlin Heidelberg",
address="Berlin",
volume="6854",
pages="520--528",
optkeywords="Validation",
optkeywords="Statistical Inference",
optkeywords="Medical Imaging Algorithms.",
abstract="Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.",
optnote="IAM; ADAS",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1676), last updated on Fri, 18 Jul 2014 10:03:59 +0200",
opturl="http://congreso.us.es/caip2011/poster2.php",
file=":http://refbase.cvc.uab.es/files/HGR2011.pdf:PDF"
}