Multimodality Medical Image Fusion using Rotated Wavelet Transform

DOI

10.2991/iccasp-16.2017.89How to use a DOI?

Keywords

Medical Image Fusion, Rotated Wavelet Transform, Discrete Wavelet Transform, Cancer Treatment, Radiotherapy, RWT filter mask, Fusion Parameters.

Abstract

This paper presents a novel approach to multimodality medical image fusion for better visualization of lesions and calcification. The algorithm utilizes source modalities as Computed Tomography (CT) and Magnetic Res-onance Imaging (MRI). It is a feature based fusion technique in which Rotated Wavelet Transform (RWT) is used for extraction of edge-related features from both the source modalities. These features are used to create new frequency domain plane using maxima and entropy based fusion rules. The fusion process is useful in the analysis of the lesions for diagnosis, treatment, and post treatment reviews. The proposed technique is evaluat-ed on the pilot study sets using objective analysis parameters like entropy, root means square error, edge quality measure, mean structural similarity index measure, etc. The fusion results of the proposed technique are com-pared with the existing fusion algorithms. The subjective analysis of the fused images by radiologists reveals that the fused images using RWT technique are superior and present all relevant anatomical structures.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - S. Chavan
AU  - A. Pawar
AU  - S. Talbar
PY  - 2016/12
DA  - 2016/12
TI  - Multimodality Medical Image Fusion using Rotated Wavelet Transform
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 616
EP  - 624
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.89
DO  - 10.2991/iccasp-16.2017.89
ID  - Chavan2016/12
ER  -