Thoracic CT-PET registration using a 3D breathing model

Authors:
Antonio Moreno;Sylvie Chambon;Anand P. Santhanam;Roberta Brocardo;Patrick Kupelian;Jannick P. Rolland;Elsa Angelini;Isabelle Bloch
Affiliations:
Ecole Nationale Supérieure des Télécommunications, GET - Télécom Paris, CNRS, UMR, LTCI, Signal and Image Processing Department, Paris, France;Ecole Nationale Supérieure des Télécommunications, GET - Télécom Paris, CNRS, UMR, LTCI, Signal and Image Processing Department, Paris, France;Optical Diagnostics and Applications Laboratory, University of Central Florida and Department of Radiation Oncology, MD Anderson Cancer Center, Orlando;Ecole Nationale Supérieure des Télécommunications, GET - Télécom Paris, CNRS, UMR, LTCI, Signal and Image Processing Department, Paris, France;Department of Radiation Oncology, MD Anderson Cancer Center, Orlando;Optical Diagnostics and Applications Laboratory, University of Central Florida;Ecole Nationale Supérieure des Télécommunications, GET - Télécom Paris, CNRS, UMR, LTCI, Signal and Image Processing Department, Paris, France;Ecole Nationale Supérieure des Télécommunications, GET - Télécom Paris, CNRS, UMR, LTCI, Signal and Image Processing Department, Paris, France
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Year:
2007

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Abstract

In the context of thoracic CT-PET volume registration, we present a novel method to incorporate a breathing model in a non-linear registration procedure, guaranteeing physiologically plausible deformations. The approach also accounts for the rigid motions of lung tumors during breathing. We performed a set of registration experiments on one healthy and four pathological data sets. Initial results demonstrate the interest of this method to significantly improve the accuracy of multimodal volume registration for diagnosis and radiotherapy applications.