Workspace:RE3 Imagerie Interventionnelle

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WORKPACKAGE 3: INTERVENTIONAL IMAGING

Interventional imaging is a fast growing field based on the constant improvement of real time image acquisition and analysis in various imaging modalities. Interventional imaging brings new clinical applications where various imaging modalities are used intra-operatively to assist medical or surgical procedures. Modern medical imaging modalities (ultrasound, fluoroscopy, CT, MRI, video, etc.) produce high resolution images of the human body that can be used to precisely guide surgical instruments or to monitor treatment in real time. Current challenges in interventional imaging are, for example, the compensation for physiological motions during image-guided interventional procedures, image-registration of moving and deformable organs, and the development of intra-operative devices.

Coordinator: Michel de Mathelin

Project Manager: Jean-François Kong

1. Navigation and augmented reality Navigation of surgical instruments consists of real time registration of the instruments with respect to anatomical landmarks or fiducials and pre-operative images (CT-scan, MRI, etc.) in order to provide the doctor an accurate positioning of the instruments during the procedure according to a pre-operative planning. The registration is often made using infrared cameras and fiducials, but can also be performed with video cameras, stereotactic markers and scanned images, or magnetic tracking devices, to cite a few techniques. Augmented reality provides pre-operative data on intra-operative images and requires a real-time registration between the intra-operative view and the pre-operative images. An important challenge is in applications to moving and deformable organs. Algorithms that can register pre-operative data on intra-operative data in a moving and deformable environment are required. Examples of applications are: compensation for brain shift during neurosurgery, or that for breathing motion in laparoscopic surgery or heart-beat tracking during cardiac surgery. Another challenge is to provide non-rigid fusion algorithms between intra-patient images from different modalities. A research issue is also the development of robust registration algorithms without the use of fiducials or markers on the patient, based only on the intra-operative images and regions of interest defined by the doctor.