Adaptive Non-Local Means Denoising Algorithm for Cone-Beam Computed Tomography Projection Images

摘要：

Aiming at the difficulty of choosing filtering parameters of Non-Local Means (NLM) denoising algorithm for Cone-Beam Computed Tomography (CBCT)projection images, an adaptive NLM denoising algorithm is proposed. First, a simplified noise estimation method based on sub-block division is proposed to replace the approach of designating the background region, which can adaptively identify the background region and estimate the noise level when the background region is changed obviously. And then an algorithm of adaptively obtaining filter strengths of projection images is proposed by analyzing the impact of filter strength to filtering result in NLM denoising algorithm, in which the filter strength is adjusted according to the characteristics of current image and the noises in all projection images are suppressed to a similar level. The experimental result shows that the proposed algorithm can accurately estimate the noise level of projection image and markedly improve the slice image quality.

关键词： non-local means noise estimation filter strength Cone-Beam Computed Tomography

作者: Kuidong Huang Dinghua Zhang Kuyu Wang Mingjun Li

作者单位: Key Lab of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education Northwestern Polytechnical University Xian, China

会议类型: 国际会议

会议名称: The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)

会议地点: 西安

会议语种:英文

页码: 33-38

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）