An Optimised Linear Mechanical Model for Estimating Brain Shift Caused by Meningioma Tumours
Hossein Yousefi,
Alireza Ahmadian,
Davood Khodadad,
Hooshangh Saberi,
Alireza Daneshmehr
Issue:
Volume 1, Issue 1, June 2013
Pages:
1-9
Received:
28 April 2013
Published:
10 June 2013
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%.
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...
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Determination of the Optimal Color Space from Eight Types of Color Spaces for Distinguishing Small Retinal Hemorrhages from Dust Artifacts
Issue:
Volume 1, Issue 1, June 2013
Pages:
10-19
Received:
10 July 2013
Published:
10 August 2013
Abstract: To determine the optimal color space from eight types of color spaces for distinguishing small retinal hemorrhages from dust artifacts in cases of early diabetic retinopathy. We constructed an experimental device, which comprised an illumination optical system and a photographic optical system separated by a mirror having a hole. This device included a canon EOS 50D camera, an EF 50 mm f/1.8–2 camera lens, a Speedlite 270EX flash, an object lens, four double-convex lenses, three aperture stops, and six artificial eyes. The hemispherical eye ground was made of polythene terephthalate, which was painted with six matt color sprays: red, coffee, ocher, yellow, ivory, and orange. Five fragments of house dust on the object lens and the two lenses were photographed under each artificial eye. The RGB color space, measured by Paint Shop Pro from pictures, was changed into seven types of color spaces: XYZ, CMY, HSL, HSV, HSI, L*a*b*, and L*u*v*. The L*u*v* color space was the optimal one as it demonstrated the highest sensitivity and the best reproducibility. This result demonstrated that this color space could distinguish small hemorrhages from dust artifacts. Next, we analyzed the L*u*v* color space and compared the following three types of house dust positions: “on an object lens,” “on a photographic optical system,” and “on an illumination optical system.” The house dust position “on an object lens” had the highest sensitivity and the best reproducibility. However, the positions “on a photographic optical system” and “on an illumination optical system” had high sensitivity and good reproducibility only under certain conditions. In addition, no differences were found among the six types of fundus colors.
Abstract: To determine the optimal color space from eight types of color spaces for distinguishing small retinal hemorrhages from dust artifacts in cases of early diabetic retinopathy. We constructed an experimental device, which comprised an illumination optical system and a photographic optical system separated by a mirror having a hole. This device includ...
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