Serial registration of intraoperative MR images of the brain

Ferrant, Matthieu; Nabavi, Arya; Macq, Benoı̂t; Black, Peter McL.; Jólesz, Ferenc A.; Kikinis, Ron; Warfield, Simon K.

doi:10.1016/s1361-8415(02)00060-9

Cited by 180 publications

(162 citation statements)

References 80 publications

(92 reference statements)

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“…using finite deformations) finite element analysis was used as a solution method in this study. However, it should be noted that a number of research laboratories have reported computing deformations of the brain undergoing the shift using geometrically linear solution methods (Miga et al 1997, Hagemann et al 1999, Warfield et al 2000, Castellano-Smith et al 2001, Ferrant et al 2001, Ferrant et al 2002, Miga et al 2000, Clatz et al 2005, Dumpuri et al 2007). Such methods assume that the brain deformations are infinitesimally small.…”

Section: Discussionmentioning

confidence: 99%

“…the brain) deformations must be taken into account. Since the late 1990s significant research effort has been directed towards the prediction of such deformations using biomechanical models (Miga et al 1997, Hagemann et al 1999, Warfield et al 2000, Ferrant et al 2001, Ferrant et al 2002, Castellano-Smith et al 2001, Xu and Nowinski 2001, Miga et al 2000, Wittek et al 2005, Dumpuri et al 2007). Typically, in such models, the Finite Element (FE) method (e.g.…”

Section: Introductionmentioning

confidence: 99%

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On the unimportance of constitutive models in computing brain deformation for image-guided surgery

Wittek

Hawkins

Miller

2008

Biomech Model Mechanobiol

106

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Imaging modalities that can be used intra-operatively do not provide sufficient details to confidently locate the abnormalities and critical healthy areas that have been identified from highresolution pre-operative scans. However, as we have shown in our previous work, high quality pre-operative images can be warped to the intra-operative position of the brain. This can be achieved by computing deformations within the brain using a biomechanical model. In this paper, using a previously developed patient-specific model of brain undergoing craniotomy-induced shift, we conduct a parametric analysis to investigate in detail the influences of constitutive models of the brain tissue. We conclude that the choice of the brain tissue constitutive model, when used with an appropriate finite deformation solution, does not affect the accuracy of computed displacements, and therefore a simple linear elastic model for the brain tissue is sufficient.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the unimportance of constitutive models in computing brain deformation for image-guided surgery

Wittek

Hawkins

Miller

2008

Biomech Model Mechanobiol

106

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“…Audette [1] measured the visible intra-operative cortex shift using a laser range scanner. Ferrant [2] extracted the full cortex and ventricles surfaces from intra-operative MR images. These interpolation-based registration methods however suffer from a decrease of accuracy when reaching internal structures far from the measured surface.…”

Section: Non-rigid Registration For Image-guided Surgerymentioning

confidence: 99%

Hybrid Formulation of the Model-Based Non-rigid Registration Problem to Improve Accuracy and Robustness

Clatz

Delingette

Talos

et al. 2005

Lecture Notes in Computer Science

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Abstract. We present a new algorithm to register 3D pre-operative Magnetic Resonance (MR) images with intra-operative MR images of the brain. This algorithm relies on a robust estimation of the deformation from a sparse set of measured displacements. We propose a new framework to compute iteratively the displacement field starting from an approximation formulation (minimizing the sum of a regularization term and a data error term) and converging toward an interpolation formulation (least square minimization of the data error term). The robustness of the algorithm is achieved through the introduction of an outliers rejection step in this gradual registration process. We ensure the validity of the deformation by the use of a biomechanical model of the brain specific to the patient, discretized with the finite element method. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift up to 13 mm.

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“…One approach is to model mechanical organ behavior based on the finite element method (FEM), as explained in [4] [5] for the case of the brain. The idea is to capture the displacement of the surface(s) defining the shape of the organ and to compute the resulting deformation of a volume mesh of this organ by linear elastic finite element (FE) calculations.…”

Section: Introductionmentioning

confidence: 99%

“…The precision achieved for deformation prediction is about 1 voxel [4]. The situation becomes more complex when the surgeon performs cuts, retractions, or resections [4] [6]. The last two necessarily involve a cut.…”

Section: Introductionmentioning

confidence: 99%

Modelling Surgical Cuts, Retractions, and Resections via Extended Finite Element Method

Vigneron

Verly

Warfield

2004

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004

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Abstract. We introduce a new, efficient approach for modelling the deformation of organs following surgical cuts, retractions, and resections. It uses the extended finite element method (XFEM), recently developed in "fracture mechanics" for dealing with cracks in mechanical parts. XFEM eliminates the computationally-expensive remeshing that would be required if the standard finite element method (FEM) was used. We report on the successful application of the method to the simulation of 2D retraction. The method may have significant impact on surgical simulators and navigators.

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Serial registration of intraoperative MR images of the brain

Cited by 180 publications

References 80 publications

On the unimportance of constitutive models in computing brain deformation for image-guided surgery

On the unimportance of constitutive models in computing brain deformation for image-guided surgery

Hybrid Formulation of the Model-Based Non-rigid Registration Problem to Improve Accuracy and Robustness

Modelling Surgical Cuts, Retractions, and Resections via Extended Finite Element Method

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