A framework for evaluating the impact of compression on registration algorithms without gold standard

Tristan Glatard 1, 2 Johan Montagnat 1 Xavier Pennec 2
1 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS
SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
2 ASCLEPIOS - Analysis and Simulation of Biomedical Images
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : The impact of lossy compression has often been discussed in the medical area. In this study, an evaluation of the impact of lossy compression on the performance of rigid registration algorithms for medical images is proposed. The robustness, repeatability and accuracy of these algorithms is estimated through a statistical procedure for each compression ratio. Results are obtained thanks to a grid technology handling the computation cost of the method. Experiments reveal that the impact of compression is quite negligible below a significant compression ratio if the registration algorithm has a good multi-scale handling. Beyond this threshold, feature-based methods are highly penalized.
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Tristan Glatard, Johan Montagnat, Xavier Pennec. A framework for evaluating the impact of compression on registration algorithms without gold standard. International Conference on Image Processing, Oct 2008, San Diego, California, United States. IEEE, pp.2912-2915, 2008, 〈10.1109/ICIP.2008.4712404〉. 〈hal-00683112〉

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