An adaptive local weighted image reconstruction algorithm for EIT/UTT dual-modality imaging

Abstract

Electrical Impedance Tomography (EIT) and Ultrasound Transmission Tomography (UTT) are widely used in industrial process detection and medical diagnosis. EIT has a higher sensitivity near the edge of the sensitive domain, while the UTT has a higher sensitivity near the center of the sensitive domain. Based on the point, high accuracy image reconstruction is feasible by fusing the EIT and UTT together. In the paper, an adaptive local-weighted image reconstruction algorithm was proposed to solve the EIT/UTT dual-modality imaging problem. In the method, an image segmentation algorithm was introduced to obtain the high-contrast EIT and UTT images, and an adaptive local weighted method is proposed to fuse the EIT and UTT images together. Since the weights in the image fusing operator are automatically selected based on the differences between the sensitivity mappings in EIT and UTT, the fusion images from the proposed method are robust to the errors in the signal modality, and are with less artifacts and noise. In order to test our method, some simulation experiments were carried out. The results show that the proposed algorithm has a higher accuracy than the conventional single-modality imaging algorithm.