3D Physics-Based Registration of 2D Dynamic MRI Data

Raffaella Trivisonne (1, 2, 3) , Igor Peterlik (2, 4) , Stéphane Cotin (1, 2) , Hadrien Courtecuisse (3, 1, 2)

1 IHU Strasbourg - L'Institut hospitalo-universitaire de Strasbourg
2 MIMESIS - Computational Anatomy and Simulation for Medicine
3 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
4 ICS / MUNI - Institute of Computer Science [Brno]

We present a method allowing for intra-operative targeting of a specific anatomical feature. The method is based on a registration of 3D pre-operative data to 2D intra-operative images. Such registration is performed using an elastic model reconstructed from the 3D images, in combination with sliding constraints imposed via Lagrange multipliers. We register the pre-operative data, where the feature is clearly detectable, to intra-operative dynamic images where such feature is no more visible. Despite the lack of visibility on the 2D MRI images, we are able both to determine the location of the target as well as follow its displacement due to respiratory motion.

Mots clés: Robotic assistance; Dynamic MRI; FEM; Non-Rigid Registration

Domaines: Informatique [cs]

Raffaella Trivisonne, Igor Peterlik, Stéphane Cotin, Hadrien Courtecuisse. 3D Physics-Based Registration of 2D Dynamic MRI Data. MMVR - Medicine Meets Virtual Reality, Apr 2016, Los Angeles, United States. ⟨hal-01254388⟩