Line and net pattern segmentation using shape modeling

Adam Huang, Gregory Nielson, Anshuman Razdan, Gerald Farin, David Capco, Page Baluch

研究成果: 雜誌貢獻會議論文同行評審

2 引文 斯高帕斯(Scopus)


Line and net patterns in a noisy environment exist in many biomedical images. Examples include: Blood vessels in angiography, white matter in brain MRI scans, and cell spindle fibers in confocal microscopic data. These piecewise linear patterns with a Gaussian-like profile can be differentiated from others by their distinctive shape characteristics. A shape-based modeling method is developed to enhance and segment line and net patterns. The algorithm is implemented in an enhancement/thresholding type of edge operators. Line and net features are enhanced by second partial derivatives and segmented by thresholding. The method is tested on synthetic, angiography, MRI, and confocal microscopic data. The results are compared to the implementation of matched filters and crest lines. It shows that our new method is robust and suitable for different types of data in a broad range of noise levels.

頁(從 - 到)171-180
期刊Proceedings of SPIE - The International Society for Optical Engineering
出版狀態已出版 - 2003
事件Visualization and Data Analysis 2003 - Santa Clara, CA, United States
持續時間: 21 1月 200322 1月 2003


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