Multiscale adaptive method for blood vessel enhancement in x-ray angiography
Zhenyu Wu, Ming Fang, JianZhong Qian, Helmut F. Schramm · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
The goal of this work is to provide a powerful computer- aided-perception tool for physicians to visualize low- contrast blood vessel structures with exquisite details and hence to facilitate the extraction of valuable diagnostic information from angiographic images. In x-ray angiography, blood vessels often exhibit low intensity contrast with respect to their surrounding soft tissues. The problem is particularly severe for fine vessel structures. A major challenge for enhancement is the ability to emphasize vessel structures without creating artifacts such as edge overshot and noise magnification. In this work, a multi-scale adaptive contrast enhancement algorithm is developed. A pyramid of intensity images is generated using wavelet decomposition. At each pyramid level, an enhancement mask is computed which captures the fine vessel structures in the image at that scale. To generate this mask, we first compute directional sensitive Laplacian which is capable of extracting fine lines with very low contrast to its surroundings. An adaptive non-linear weighting function is then applied to the Laplacian to form an enhancement mask. The non-linearity is crucial for virtually eliminating edge overshots. These masks are then combined recursively to form a single composite mask of full resolution. Finally, the enhanced image is obtained by adding this composite mask to the original image. Extensive testing demonstrates remarkable contrast improvement in blood vessels without noticeable artifacts.