Vincent Auvray's home page (Version francaise)

Address

Email: Vincent.Auvray@irisa.fr / Vincent.Auvray@med.ge.com Address: IRISA / INRIA Rennes Campus Universitaire de Beaulieu 35042 Rennes Cedex - FRANCE Tel: +33 2.99.84.71.67 Fax: +33 2.99.84.71.71 Secretary: +33 2.99.84.72.52 (Huguette Béchu)

Vitae
Detailed resume in pdf format.

Graduated from the prestigious french engineering school Ecole Centrale de Paris, I have also carried on signal processing studies (Elektrotechnik Fachrichtung Techniche Informatik) in Germany during two years thanks to an exchange program. I have thus also graduated from the RWTH Aachen University. Both diploms are equivalent to master degrees.

I ended up my education with a six month research project (the Diplomarbeit) in the Institute for Image Processing LfB, which is specialized in medical image processing. I had to define at which optimal resolution human tissue samples had to be imaged to allow for an efficient automatic cancer cell detection.
I carried out this work in two times: I have developed an original interpolation method simulating the behavior of the microscope, and I have imagined an automatic cancer cell detection sheme to apply in the reconstructed images. This last point composes one of the steps of the detection sheme presented by the lab at ICIP'05.

Eager to stay in the medical imaging environment, I have worked during one year as an engineer in the Image Quality team by General Electric Healthcare in Paris. I decided then to apply to the phD that GE Healthcare opened in partnership with the IRISA about noise reduction in fluoroscopic images by filtering in the direction of the motion. My tutor by General Electric is Jean Liénard, and I am monitored in the VISTA project of the IRISA by Patrick Bouthemy. (Back)

Research interests

In vascular exams with digital radiography, the interventions are carried out under limited radiation, producing relatively noisy and low-contrasted images. The topic of my research is to make the temporal denoising filters robust to the motions in the images.
(More on the problem statement)

The major originality of these motion estimation and compensation tasks is to deal with transparent images. The PhD is structured in two parts: the development of motion estimation techniques specific to transparent images, that are robust to noise, and the use of this motion information to temporally denoise the clinical sequences.
(More on our contribitions, including some demos!)

Key words: object tracking, transparent images, multiple motions, denoising.
phD topic: Fluoroscopic noise reduction by filtering in the motions' direction.

Publications

V. Auvray, P. Bouthemy, J. Lienard. Transparent motion estimation in X-Ray image sequences. In IEEE Transactions on Medical Imaging. Submitted.