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Automatic guidance of robotized 2D ultrasound probes with visual servoing based on image moments.

This dissertation presents a new 2D ultrasound-based visual servoing method. The main goal is to automatically guide a robotized 2D ultrasound probe held by a medical robot in order to reach a desired cross-section ultrasound image of an object of interest. This method allows to control both the in-plane and out-of-plane motions of a 2D ultrasound probe. It makes direct use of the 2D ultrasound image in the visual servo scheme, where the feed-back visual features are combinations of image moments. To build the servo scheme, we develop the analytical form of the interaction matrix that relates the image moments time variation to the probe velocity. That modeling is theoretically verified on simple shapes like spherical and cylindrical objects. In order to be able to automatically position the 2D ultrasound probe with respect to an observed object, we propose six relevant independent visual features to control the 6 degrees of freedom of the robotic system. Then, the system is endowed with the capability of automatically interacting with objects without any prior information about their shape, 3D parameters, nor 3D location. To do so, we develop on-line estimation methods that identify the parameters involved in the built visual servo scheme. We conducted both simulation and experimental trials respectively on simulated volumetric objects, and on both objects and soft tissues immersed in a water-filled tank. Successful results have been obtained, which show the validity of the developed methods and their robustness to different errors and perturbations especially those inherent to the ultrasound modality. Keywords: Medical robotics, visual servoing, 2D ultrasound imaging, kinematics modeling, model-free servoing.

Identiferoai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00476718
Date25 March 2010
CreatorsMebarki, Rafik
PublisherUniversité Européenne de Bretagne
Source SetsCCSD theses-EN-ligne, France
LanguageEnglish
Detected LanguageEnglish
TypePhD thesis

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