Paper
26 March 2008 Pyramidal flux in an anisotropic diffusion scheme for enhancing structures in 3D images
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Abstract
Pyramid based methods in image processing provide a helpful framework for accelerating the propagation of information over large spatial domains, increasing the efficiency for large scale applications. Combined with an anisotropic diffusion scheme tailored to preserve the boundaries at a given level, an efficient way for enhancing large structures in 3D images is presented. In our approach, the partial differential equation defining the evolution of the intensity in the image is solved in an explicit scheme at multiple resolutions in an ascending-descending cycle. Intensity 'flux' between distant voxels is allowed, while preserving borders relative to the scale. Experiments have been performed both with phantoms and with real data from 3D Transrectal Ultrasound Imaging. The effectiveness of the method to remove speckle noise and to enhance large structures such as the prostate has been demonstrated. For instance, using two scales reduces the computation time by 87% as compared to a single scale. Furthermore, we show that the boundaries of the prostate are mainly preserved, by comparing with manually outlined edges.
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Oscar Acosta, Hans Frimmel, Aaron Fenster, Olivier Salvado, and Sébastien Ourselin "Pyramidal flux in an anisotropic diffusion scheme for enhancing structures in 3D images", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691429 (26 March 2008); https://doi.org/10.1117/12.771862
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KEYWORDS
3D image processing

Prostate

Anisotropic diffusion

Diffusion

Signal to noise ratio

Image filtering

Image processing

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