RESEARCH ARTICLE
Medical Images Fusion with Patch Based Structure Tensor
Fen Luo*, Jiangfeng Sun , Shouming Hou
Article Information
Identifiers and Pagination:
Year: 2015Volume: 9
First Page: 199
Last Page: 203
Publisher ID: TOBEJ-9-199
DOI: 10.2174/1874120701509010199
Article History:
Received Date: 10/4/2015Revision Received Date: 20/5/2015
Acceptance Date: 15/6/2015
Electronic publication date: 31/8/2015
Collection year: 2015
open-access license: This is an open access article licensed under the terms of the (https://creativecommons.org/licenses/by/4.0/legalcode), which permits unrestricted, noncommercial use, distribution and reproduction in any medium, provided the work is properly cited.
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.