Mr. Dongjin Kwon Profile

Dongjin Kwon

at Seoul National Univ

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Proceedings Article | 11 March 2008 Paper

Fast multiscale vessel enhancement filtering

Dong Hye Ye, Dongjin Kwon, Il Dong Yun, Sang Uk Lee

Proceedings Volume 6914, 691423 (2008) https://doi.org/10.1117/12.770038

KEYWORDS: 3D image processing, Image filtering, Convolution, 3D image enhancement, Image segmentation, Image enhancement, Gaussian filters, Medical imaging, Visualization, Liver

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This paper describes a fast multi-scale vessel enhancement filter in 3D medical images. For efficient review of the vascular information, clinicians need rendering the 3D vascular information as a 2D image. Generally, the maximum intensity projection (MIP) is a useful and widely used technique for producing a 2D image from the 3D vascular data. However, the MIP algorithm reduces the conspicuousness for small and faint vessels owing to the overlap of non-vascular structures. To overcome this invisibility, researchers have examined the multi-scale vessel enhancement filter based on a combination of the eigenvalues of the 3D Hessian matrix. This multi-scale vessel enhancement filter produces higher contrast. However, it is time-consuming and requires high cost computation due to large volume of data and complex 3D convolution. For fast vessel enhancement, we propose a novel multi-scale vessel enhancement filter using 3D integral images and 3D approximated Gaussian kernel. This approximated kernel looks like cube but it is not exact cube. Each layer of kernel is approximated 2D Gaussian second order derivative by dividing it into three rectangular regions whose sum is integer. 3D approximated kernel is a pile of these 2D box kernels which are normalized by Frobenius norm. Its size fits to vessel width in order to achieve better visualization of the small vessel. Proposed method is approximately five times faster and produces comparable results with previous multi-scale vessel enhancement filter.

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