Segmentation of Pulmonary Nodules Based on Statistic Features of Wavelet Coefficients and Dual Level Sets
A major problem of pulmonary nodules segmentation cant be solved well by conventional methods, which is other tissue in chest CT image slices, such as blood vessels and bronchi, often overlap with the nodules and they also have the same gray scale intensity approximately, for big size (＞40pixels) nodules especially. This paper presents a novel approach to solve above problem, which works in two main steps: ①Transition Region (TR ) , which is defined as the ambiguous region between nodule and background, is ascertained depending on statistic features of wavelet coefficients.② Precise boundaries of the nodule is segmented based on an improvement of dual level sets method. The validity of the proposed approach is demonstrated in the chest CT images. Experiments with real chest CT images confirm the high accuracy of our approach.
wavelet transform dual level sets image segmentation chest CT image pulmonary nodules.
Hui-yan Jiang Zhen-yu Cheng
Computing Center, Northeastern University, Shenyang 110004, China
国际会议
北京
英文
652-655
2007-05-23（万方平台首次上网日期，不代表论文的发表时间）