title: Medical Images Fusion with Patch Based Structure Tensor.
abstract: Nowadays medical imaging has played an important role in clinical use, which provide important clues for medical diagnosis. In medical image fusion, the extraction of some fine details and description is critical. To solve this problem, a modified structure tensor by considering similarity between two patches is proposed. The patch based filter can suppress noise and add the robustness of the eigen-values of the structure tensor by allowing the use of more information of far away pixels. After defining the new structure tensor, we apply it into medical image fusion with a multi-resolution wavelet theory. The features are extracted and described by the eigen-values of two multi-modality source data. To test the performance of the proposed scheme, the CT and MR images are used as input source images for medical image fusion. The experimental results show that the proposed method can produce better results compared to some related approaches.
authors.affiliation: School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, China.
authors.forename: Fen
authors.initials: F
authors.lastname: Luo
authors.affiliation: School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, China.
authors.forename: Jiangfeng
authors.initials: J
authors.lastname: Sun
authors.affiliation: School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, China.
authors.forename: Shouming
authors.initials: S
authors.lastname: Hou
keywords: Medical image fusion; patch similarity; structure tensor; wavelet decomposition