Abstract
Juxtapleural nodules were excluded from the segmented lung region in the Hounsfield unit threshold-based segmentation method. To re-include those regions in the lung region, a new approach was presented using scale-invariant feature transform and gradient vector flow models in this study. First, the scale-invariant feature transform method was utilized to detect all scale-invariant points in the binary lung region. The boundary points in the neighborhood of a scale-invariant point were collected to form the supportive boundary lines. Then, we utilized a Fourier descriptor to obtain a character representation of each supportive boundary line. Spectrum energy recognizes supportive boundaries that must be corrected. Third, the gradient vector flow-snake method was presented to correct the recognized supportive borders with a smooth profile curve, giving an ideal correction edge in those regions. Finally, the performance of the proposed method was evaluated through experiments on multiple authentic computed tomography images. The perfect results and robustness proved that the proposed method could correct the juxtapleural region precisely.
Funder
National Natural Science Foundation of China
the Science and Technology Development Program of Tai’an
Publisher
Public Library of Science (PLoS)
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献