A novel lung nodules detection scheme based on vessel segmentation on CT images

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Abstract

Lung vessels often interfere with the detection of lung nodules. In this paper, a novel computer-Aided lung nodule detection scheme on vessel segmentation is proposed. This paper describes an active contour model which can combine image region mean gray value and image edge energy. It is used to segment and remove lung vessels. A selective shape filter based on Hessian Matrix is used to detect suspicious nodules and remove omitted lung vessels. This paper extracts density, shape and position features of suspicious nodules, and uses a Rule-Based Classification (RBC) method to identify true positive nodules. In the experiment results, the detection sensitivity is about 90% and FP is 1/scan.

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Jia, T., Zhang, H., & Meng, H. (2014). A novel lung nodules detection scheme based on vessel segmentation on CT images. In Bio-Medical Materials and Engineering (Vol. 24, pp. 3179–3186). IOS Press. https://doi.org/10.3233/BME-141139

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