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Träfflista för sökning "WFRF:(Ahmadian Alireza) srt2:(2013)"

Sökning: WFRF:(Ahmadian Alireza) > (2013)

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1.
  • Yousefi, Hossein, et al. (författare)
  • An optimised linear mechanical model for estimating brain shift caused by meningioma tumours
  • 2013
  • Ingår i: International Journal of Biomedical Science and Engineering. - : Science Publishing Group. - 2376-7227 .- 2376-7235. ; 1:1, s. 1-9
  • Tidskriftsartikel (refereegranskat)abstract
    • Estimation of brain deformation plays an important role in computer-aided therapy and image-guided neurosurgery systems. Tumour growth can cause brain deformation and change stress distribution in the brain. Biomechanical models exist that use a finite element method to estimate brain shift caused by tumour growth. Such models can be categorised as linear and non-linear models, both of which assume finite deformation of the brain after tumour growth. Linear models are easy to implement and fast enough to for applications such as IGS where the time is a great of concern. However their accuracy highly dependent on the parameters of the models in this paper, we proposed an optimisation approach to improve a naive linear model to achieve more precise estimation of brain displacements caused by tumour growth. The optimisation process has improved the accuracy of the model by adapting the brain model parameters according to different tomour sizes.We used patient-based tetrahedron finite element mesh with proper material properties for brain tissue and appropriate boundary conditions in the tumour region. Anatomical landmarks were determined by an expert and were divided into two different sets for evaluation and optimisation. Tetrahedral finite element meshes were used and the model parameters were optimised by minimising the mean square distance between the predicted locations of the anatomical landmarks derived from Brain Atlas images and their actual locations on the tumour images. Our results demonstrate great improvement in the accuracy of an optimised linear mechanical model that achieved an accuracy rate of approximately 92%.
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2.
  • Khodadad, Davood, et al. (författare)
  • CT and PET Image Registration : Application to Thorax Area
  • 2013
  • Ingår i: International Journal of Image and Graphics. - : EJournal Publishing. - 0219-4678 .- 2301-3699. ; 1:4, s. 171-175
  • Tidskriftsartikel (refereegranskat)abstract
    • Accurate attenuation correction of emission data is mandatory for quantitative analysis of PET images. One of the main concerns in CT-based attenuation correction (CTAC) of PET data in multimodality PET/CT imaging is misalignment occurred due to respiratory artifact between PET and CT images. In this paper a combined method which is simple and fast is proposed for registration of PET and CT data to correct the effect of this artifact. The algorithm is composed of two step: First step is meant to reduce the noise by applying an adaptive gradient anistropic diffusion filter then using Iterative closest point (ICP) registration method in order to obtain initial estimation to ensure fast and accurate convergence of the algorithm. At the second step, the respiratory related artifact of PET images is greatly reduced by employing Free Form Deformation algorithm based on B-spline which provides more accurate adaptive transformation to align the images
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  • Resultat 1-2 av 2

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