Medical Image Processing with Spiking Neural P Systems
摘要
SNP systems provide an effective solution for processing large-scale medical image data with its parallelism, discreteness, distribution, and scalability. This chapter explores the potential application of SNP systems in medical image processing. We first discusses medical image processing and main tasks, including image registration, segmentation, and prediction. Then, we present two self-learning algorithms based on SNP systems, one for medical image segmentation, taking magnetic resonance imaging (MRI) images of brain tumors as an example, and the other for overall survival time prediction on histopathology whole slide images. Concluding remarks are finally given.