APPLICATION OF GRAY SYSTEM THEORY IN MRI CLASSIFICATION
Chuin-Mu Wang, Tsung‐Hung Lin, Ruey‐Maw Chen, Sheng-Chih Yang · Biomedical Engineering Applications Basis and Communications · 2010
This article presents a new multispectral signature detection approach to magnetic resonance (MR) image classification. It is called the gray system theory (GST) method. In recent years, although GST has been used in various fields, applying the GST to medical images is very rare. The theoretical basis of GST is the gray hazy set; the main element is composed of an uncertain or abstract set and through a series of algorithms, the gray messages or phenomena are transformed into white ones. The concept of the theory is based on the information coverage, which establishes a new regular set based on source data and then the set is mapped to a 2D space. A series of experiments are conducted and compared to the commonly used fuzzy C-means (FCM) method, extension theory, and perceptron for performance evaluation. The results show that the GST method is a promising and effective spectral technique for MR image classification.