Segmentation of Pulmonary Nodules Based on Statistic Features of Wavelet Coefficients and Dual Level Sets

A major problem of pulmonary nodules segmentation can't 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: (1) transition 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.

[1]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[2]  Baba C. Vemuri,et al.  A fast level set based algorithm for topology-independent shape modeling , 1996, Journal of Mathematical Imaging and Vision.

[3]  Ning Cheng,et al.  New Elevated Source/Drain for NMOS Process Using Chlorine Gas Etching : Batch Type Si Etching with Damage Free and Very High Selectivity , 2006 .

[4]  Jiang Hui-yan,et al.  Segmentation of Pulmonary Nodules Based on Improved Dual Fast Marching Method , 2007 .

[5]  Rachid Deriche,et al.  Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Yoshiaki Nemoto,et al.  Increasing Efficiency of DoS-Attack Traceback over Mobile Networks , 2006 .

[7]  Rachid Deriche,et al.  Adaptive Segmentation of Vector Valued Images , 2003 .

[8]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[9]  Nobuyuki Otsu,et al.  ATlreshold Selection Method fromGray-Level Histograms , 1979 .

[10]  Max A. Viergever,et al.  Computer-aided diagnosis in chest radiography: a survey , 2001, IEEE Transactions on Medical Imaging.

[11]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[12]  Jiang Hui-yan,et al.  Automated Segmentation of Lung Lobes and Recognition of Pulmonary Nodules from Multi-slice Chest X-ray CT Images , 2007 .

[13]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Hiroshi Fujita,et al.  Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique , 2001, IEEE Transactions on Medical Imaging.