Integration of Spatial and Transform Domain Technique for the Multimodal Medical Image Fusion
S. Sandhya1, M. Senthil Kumar2, B. Chidambararajan3
1S. Sandhya, Assistant Professor, SRM Valliammai Engineering College, Chennai (Tamil Nadu), India.
2Dr. M. Senthil Kumar, Associate Professor, SRM Valliammai Engineering College, Chennai (Tamil Nadu), India.
3Dr. B. Chidambararajan, Professor Principal, SRM Valliammai Engineering College, Chennai (Tamil Nadu), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 642-646 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11370283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the area of medical image processing, multi-modality medical image-fusion plays a vital role as it is helpful in understanding the organs of human captured through different modalities like MRI, CT, PET and etc., In this paper, the proposed approach implements a hybrid fusion algorithm for the medical images obtained from multiple modalities using 2DPCA and curvelet transform. The hybrid fusion is useful in improving the quality of the medical images and it is greatly helpful in medical diagnosis and treatment. PCA is used to obtain the most important features from the images. It can be used for isolation or it can be combined with other image fusion methods. The proposed scheme applies 2DPCA a variation of PCA (Principal Component Analysis) which is a dimension-reduction method. In contrast to PCA, 2DPCA directly works on the two dimensional images without any vectorization. Curvelet transform is an image segmentation oriented technique which divides the input image into tiles on which ridgelet transform is applied to for the process of edge detection. The performance of the hybrid fusion algorithm is evaluated against the quality metrics and it is shown that the proposed scheme works better than the existing method.
Keywords: Medical Image Processing, Multi-Modal Medical Image, MRI, PET, CT, PCA, 2DPCA, Curvelet Transform.
Scope of the Article: Image Security