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Purpose:To develop a postprocessing algorithm that enhances the visibility of intracranial venous vasculature and reduces the artifacts in the display of susceptibility‐weighted images (SWI).
Materials and Methods:Image‐domain high‐pass filters based on second‐order phase difference were applied to the complex 3D SWI data to enhance the susceptibility phase shift of the veins and suppress background...
To enhance the visibility of veins of the brain in susceptibility weighted imaging (SWI)-based MR venography using a 3D multi-scale vessel enhancement filter. The magnitude data of SWI were convolved with the second-order derivatives of the Gaussian function. Eigenvalue analysis of the Hessian matrix of the convolved magnitude images was used to enhance the veins. Multi-scale integration was formulated...
An improved version of the variational level set algorithm was used for volume segmentation of susceptibility weighted images of the brain. Binary maps based on an intensity histogram were used as edge indicators in the level set evolution equation. The parameters of the evolution equation were optimized with a synthetic SWI phantom using a simulated annealing algorithm. The convergence condition...
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