Pulmonary vascular tree enhancement with an improved shock diffusion filter

Filtering of vessel structures with the second order information is a fundamental basis for vascular tree enhancement. Traditional Hessian-related methods often suffer from noise pollution and variance of grey level. In this paper an improved shock diffusion filter is proposed to enhance vascular structures. By using multi-scale vesselness measurement as a regulation factor in the diffusion process, this filter expresses a high response to vesselness and robust anti-noise ability. The proposed filtering method is validated with both synthetic data and pulmonary CT data. The results show that the proposed method is robust with noisy image and effective in enhancing vessel bifurcations.