Spiculation Sign Recognition in a Pulmonary Nodule Based on Spiking Neural P Systems

• Main Authors: Shi Qiu, Jingtao Sun, Tao Zhou, Guilong Gao, Zhenan He, Ting Liang
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2020/6619076

The spiculation sign is one of the main signs to distinguish benign and malignant pulmonary nodules. In order to effectively extract the image feature of a pulmonary nodule for the spiculation sign distinguishment, a new spiculation sign recognition model is proposed based on the doctors’ diagnosis process of pulmonary nodules. A maximum density projection model is established to fuse the local three-dimensional information into the two-dimensional image. The complete boundary of a pulmonary nodule is extracted by the improved Snake model, which can take full advantage of the parallel calculation of the Spike Neural P Systems to build a new neural network structure. In this paper, our experiments show that the proposed algorithm can accurately extract the boundary of a pulmonary nodule and effectively improve the recognition rate of the spiculation sign.