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

Abstract EN

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.