Regions Preserving Edge Enhancement for Multisensor-Based Medical Image Fusion
Kangjian He, Jian Gong, Lisiqi Xie, Xuejie Zhang, Dan Xu
Abstract
Multimodal medical image fusion technology has been widely used in various applications of clinical diagnosis, which aims to provide richer information by integrating effective features of multiple medical images. In this article, a novel fusion scheme based on region-preserving edge enhancement is proposed for medical images. The overlapping regions of source images that need to be fused are detected first. Next, according to the different visual features, the overlapping map is divided by Fuzzy c-means (FCM)-based algorithm. Then, different fusion strategies based on visual saliency and texture details are proposed for region-preserving and edge enhancement. Experimental results show that the proposed scheme can effectively highlight the visual features and retain key information. Furthermore, the performance of different medical images also demonstrates that the proposed method can obtain better results than those achieved by some of the state-of-the-art methods.