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Reconstruction de la déformée d’une aiguille instrumentée

Abstract : Most of navigation system dedicated to interventional radiology make the assumption that needles stay straight during insertions in tissues. In practice, this hypothesis is not verified as the interactions between needles and surrounding tissues cause the needles to bend, resulting in a loss of accuracy. My PhD thesis is a part of the national projet GAME-D whose goal is to solve that problem by developing and studying instrumented needles which should eventually provide 3D deformed shape of the needle to clinicians in real-time. My reasearch work focus on reconstruction of deformed needle shape from its strain sensors data. Precision needed for clinical use faces technical limitations which restraint number of sensors embedded on the needle. Methods developped to adress this issue fall into one of these two categories: sensors data retrieving and sensors data processing. Use of beam theory to study sensors deformations gives strain information such as torsion. It also allows to develop reconstruction methods able to use these informations to gain accuracy. An optimization method of the sensors positions based on needle insertions experimental data is proposed. Sensors optimal positions make sensors data much more significant. A statistical processing of experimental data is performed to extract deformation features of needles in tissue. It is further used in a a specially built reconstruction method. Representativeness of these features improve the reconstrution of the deformed shape of the needle.
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Submitted on : Thursday, January 25, 2018 - 12:08:10 PM
Last modification on : Wednesday, October 7, 2020 - 1:20:04 PM
Long-term archiving on: : Friday, May 25, 2018 - 6:00:55 AM


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  • HAL Id : tel-01692611, version 1


Pierre-Loup Schaefer. Reconstruction de la déformée d’une aiguille instrumentée. Mathématiques générales [math.GM]. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAS025⟩. ⟨tel-01692611⟩



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