Abstract
CT perfusion imaging is used for the follow-up of abdominal tumors. A specificity of our work is that patients are breathing freely during image acquisition (5 minutes). We propose an automatic 3D image registration to compensate for respiratory motion. The registration is computed in two main steps: global translation in the z-direction and 3D multiresolution blockmatching. Within this algorithm, the choice of similarity measure largely determines the algorithm robustness in presence of intensity shifts due to contrast diffusion. We exploit a modified entropy-based similarity measure to improve the quality of registration. We also propose two relevant criteria allowing to quantify the registration quality: one based on the gradients of difference images and one based on the smoothness of enhanced-intensity curves.
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Romain, B., Letort, V., Lucidarme, O., d’Alché-Buc, F., Rouet, L. (2012). Registration of Free-Breathing Abdominal 3D Contrast-Enhanced CT. In: Yoshida, H., Hawkes, D., Vannier, M.W. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2012. Lecture Notes in Computer Science, vol 7601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33612-6_29
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DOI: https://doi.org/10.1007/978-3-642-33612-6_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33611-9
Online ISBN: 978-3-642-33612-6
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