A spatiotemporal neural network on dynamic Gd-enhanced MR images for diagnosing recurrent nasal papilloma

The purpose of this paper is to develop an automatic diagnosis system for distinguishing between tumor and fibrosis in the nasal region. The proposed system is composed of a new model, Relative Intensity Change (RIC), for point matching among the consecutive MR image sequence, and a Spatiotemporal Neural Network (STNN) for distinguishing between the tumor and fibrosis. Then, a knowledge-based refinement process is applied for extracting the tumor/fibrosis. A color-code representation of the different abnormal regions are displayed. The experimental results show that the proposed method is able to detect the abnormal tissues precisely.