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
2 ASCLEPIOS - Analysis and Simulation of Biomedical Images

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.

Domaines: Calcul parallèle, distribué et partagé [cs.DC]; Imagerie médicale; Modélisation et simulation; Traitement du signal et de l'image [eess.SP]; Imagerie; Traitement du signal et de l'image [eess.SP]

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. pp.2912-2915, ⟨10.1109/ICIP.2008.4712404⟩. ⟨hal-00683112⟩