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University of Auvergne
ALCoV (Advanced Laparoscopy and Computer Vision group), ISIT, UMR6284 CNRS / Univ. d’Auvergne

MSc / BSc Projects in France: Does elastography imaging support 3D reconstruction in laparoscopy?

about 500 Euros/month
ALCoV is a CNRS research group at Université d’Auvergne researching in computer vision in the application of computer-assisted surgery (CAS). CAS supports not only planning of the surgical procedure but also in performing the surgery. A particular research topic of the ALCoV group is to support CAS with the development of Augmented Reality (AR). The main application is the visualisation of pre-operative images such as from Magnetic Resonance Imaging (MRI) during laparoscopy in real-time. To realize this, we use the mechanism of Shape-from-Template (SfT). SfT, for which we already have efficient implementations, combines object detection and 3D reconstruction. One of the current issues is the non-isometric deformation of the organs. It seems obvious that harder tissues deform less than softer tissues. Prior
knowledge of the tissue elasticity can be captured using recently developed Magnetic Resonance Elastography (MRE) imaging. However, so far the elastographic information is not considered in the SfT models.

Thus, this internship aims to investigate the deformation of test objects with various elasticities and to include the elastographic data as derived from MRE in the SfT models. The intern will develop a simple measurement setup to apply a reproducible deformation onto the measurement objects. The objects should be imaged during the various stages of the deformation to define a rule for their deformation relative to their elasticity. Using the SfT-toolbox this project aims to extend the toolbox by algorithms considering the elasticity of the objects. If successful, the algorithms will be verified on
in-vivo data. The end results would be a machine which would, in real-time, detect and reconstruct the deforming uterus in 3D from the laparoscopic video stream captured by a simple camera.

Despite improving the quality of laparoscopy and therewith patient's recovery, the results, if successful, may lead to a scientific publication. A scientific publication will be a plus for the intern's future academic career.

Requirements:
Basic knowledge of computer vision (e.g. camera models and 3D rendering) as well as good coding skills (MATLAB, C++).

Application deadline:
The position is open till it is filled.

Shape-from-Template. A. Bartoli, Y. Gérard, F. Chadebecq, T. Collins and D. Pizarro. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015.
High-resolution tensor MR elastography for breast tumour detection. Sinkus, R., Lorenzen, J., Schrader, D., Lorenzen, M., Dargatz, M., & Holz, D. Physics in medicine and biology, 2000.
Bewerbungsschluss: 01.01.2017 Erschienen auf academics.de am 04.11.2016
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