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Brain mr Image segmentation for the construction of an anatomical model dedicated to mechanical simulation

Abstract : The general problem that motivates the work developed in this thesis is: how to obtain anatomical information during a neurosurgery?. Magnetic Resonance (MR) images are usually acquired before the surgery to provide anatomical information for diagnosis and planning. Also, the same images are commonly used during the surgery, because to acquire MRI images in the operating room is complex and expensive. To make these images useful inside the operating room, a registration between them and the patient's position has to be processed. The problem is that the brain suffers deformations during the surgery, in a process called brain shift, degrading the quality of registration. To correct this, intra-operative information may be used, for example, the position of the brain surface or US images localized in 3D. The new registration will compensate this problem, but only to a certain extent. Mechanical models of the brain have been developed as a solution to improve this registration. They allow to estimate brain deformation under certain boundary conditions. In the literature, there are a variety of methods for implementing these models, different equation laws used for continuum mechanic, and different reported mechanical properties of the tissues. However, a patient specific anatomical model is always required. Currently, most mechanical models obtain the associated anatomical model by manual or semi-manual segmentation. The aim of this thesis is to propose and implement an automatic method to obtain a model of the brain fitted to the patient's anatomy and suitable for mechanical modeling. The implemented method uses deformable model techniques to segment the most relevant anatomical structures for mechanical modeling. Indeed, the internal membranes of the brain are included: falx cerebri and tentorium cerebelli. Even though the importance of these structures is stated in the literature, only a few of publications include them in the model. The segmentation obtained by our method is assessed using the most used online databases. In addition, a 3D model is constructed to validate the usability of the anatomical model in a Finite Element Method (FEM). And the importance of the internal membranes and the variation of the mechanical parameters is studied.
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Submitted on : Wednesday, October 31, 2012 - 12:57:13 PM
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  • HAL Id : tel-00747448, version 1

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Francisco José Galdames. Brain mr Image segmentation for the construction of an anatomical model dedicated to mechanical simulation. Human health and pathology. Université de Grenoble, 2012. English. ⟨NNT : 2012GRENS007⟩. ⟨tel-00747448⟩

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