Elastic registration of medical images using finite element meshes

Grabowski, Hans

doi:10.1007/978-3-642-58775-7_26

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…The tank model, which was segmented for a CT scan, clearly showed that this assumption was tenuous and was treated accordingly. The use of MRI images in itself presents a problem as MRI images could be distorted up to 5 mm (Maurer et al 1996, Grabowski et al 1998.…”

Section: Discussionmentioning

confidence: 99%

Generating accurate finite element meshes for the forward model of the human head in EIT

Tizzard

Horesh²,

Yerworth³

et al. 2005

Physiol. Meas.

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The use of realistic anatomy in the model used for image reconstruction in EIT of brain function appears to confer significant improvements compared to geometric shapes such as a sphere. Accurate model geometry may be achieved by numerical models based on magnetic resonance images (MRIs) of the head, and this group has elected to use finite element meshing (FEM) as it enables detailed internal anatomy to be modelled and has the capability to incorporate information about tissue anisotropy. In this paper a method for generating accurate FEMs of the human head is presented where MRI images are manually segmented using custom adaptation of industry standard commercial design software packages. This is illustrated with example surface models and meshes from adult epilepsy patients, a neonatal baby and a phantom latex tank incorporating a real skull. Mesh quality is assessed in terms of element stretch and hence distortion.

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Section: Discussionmentioning

confidence: 99%

Generating accurate finite element meshes for the forward model of the human head in EIT

Tizzard

Horesh²,

Yerworth³

et al. 2005

Physiol. Meas.

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show abstract

“…Our challenge was to build a system where both the visualisation ond the calculation of the change of the intracranial volume can be done very fast. Therefore, we decided to take finite element meshes generated from the stack of CT-images using a three dimensional meshing algorithm, which has been part of our previous work [5,6]. The algorithm can be divided into four parts:…”

Section: Mesh Generationmentioning

confidence: 99%

Simulation of frontal orbital advancement

et al. 1999

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Abstract:In this paper, we present a systern for performing a complex surgical intervention using virtual reality (VR) technology. With the aid of the system, the intervention can be planned and simulated exactly before performing it in reality and important additional information can be achieved during the simulation. Before working in VR, finite element models of the patient's head are generated form CTqmages. Based on these models, additional work is done in VR, where the patient's skull is cut into several pieces, which are then re-positioned. Based on moving and shifting the obtained pieces, the goal is to increase the VQiume inside the skull, which is called intracranial volume. Until now, it was not possible to measure the achieved increase of the intracranial volume. However, by using our system is it now possible to calculate this volume online during each step of our virtual intervention. The obtained results are used for the surgical intervention in reality.

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“…This can result in problems in the automatic registration process, needing manual adjustment. The use of deformable image models using finite element meshes [5] may be a possible solution but needs further investigation.…”

Section: Fig 4 Leftmentioning

confidence: 99%

Synthetic Image Modalities Generated from Matched CT and MRI Data: A New Approach for Using MRI in Brachytherapy

Krempien

Grabowski

Harms

et al. 1999

Medical Image Computing and Computer-Assisted Intervention – MICCAI’99

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Abstract. Target definition and dosimetric evaluation of brachytherapy procedures is crucial in developing proper technique and has prognostic implications. Accurate definition of tumour volume and organs at risk is essential for treatment planing. CT accurately localise sources, but often poorly delineates tumour volume. Magnetic resonance imaging (MRI) has introduced several imaging benefits such as improved soft tissue definition and unrestricted multiplanar and volumetric imaging. However, MRI has not yet seriously challenged CT for brachytherapy planing in most sites. One main reasons for this is the poor imaging of the applicator dummy markers required for detecting the source dwell positions. Therefore a new system generating synthetic image modalities from matched and fused CT and MRI-data has been developed. The system presented consists of five modules serving for viewing, matching, segmentation, fusion and validation. With the presented new system manual or automatic image registration and fusion of CT and MR-images can be done, enabling the use of the imaging advantages of MRI and CT in brachytherapy planing. Tumour structures or source dwell positions could be measured in any plane in one imaging modality and then copied into the other. With synthetic image-based brachytherapy planing a optimisation of target volume covering and dose distribution to treatment volume and structures at risk could be achieved. These preliminary data show that image registration and fusion is feasible for brachytherapy planing. The procedure integrating synthetic images from CT and MRI into brachytherapy planing has the advantage of precise target volume definition and of better determination of dose within this target taking into account the critical dose at structures at risk. Synthetic images may lead to an improved tumour control and reduced side effects by brachytherapy. 1 The work is partly being funded by the 'Sonderforschungsbereich Informationstechnik in der MedizinRechner-und sensorgestütze Chirurgie' of the Deutsche Forschungsgemeinschaft 964 R. Krempien et al.

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Elastic registration of medical images using finite element meshes

Cited by 4 publications

References 2 publications

Generating accurate finite element meshes for the forward model of the human head in EIT

Generating accurate finite element meshes for the forward model of the human head in EIT

Simulation of frontal orbital advancement

Synthetic Image Modalities Generated from Matched CT and MRI Data: A New Approach for Using MRI in Brachytherapy

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