Multi-Modal Medical Image Fusion using Multi-Resolution Discrete Sine Transform

Naidu, VPS and Divya, M and Maha Lakshmi, P (2017) Multi-Modal Medical Image Fusion using Multi-Resolution Discrete Sine Transform. Control and Data Fusion e-Journal, Vol. 1 ( No. 2). pp. 13-26.

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Quick advancement in high innovation and current medical instrumentations, medical imaging has turned into a fundamental part in many applications such as in diagnosis, research and treatment. Images from multimodal imaging devices usually provide complementary and sometime conflicting information. Information from one image may not be adequate to give exact clinical prerequisites to the specialist or doctor. Of-late, Multi-Model medical image fusion playing a challenging role in current research areas. There are many theories and techniques developed to fuse the multimodal images by researchers. In this paper, introducing a new algorithm called as Multi Resolution Discrete Sine Transform which is used for Multi-Model image fusion in medical applications. Performance and evaluation of this algorithm is presented. The main intention of this paper is to apply DST which is easy to understand and demonstrated method to process image fusion techniques. The proposed MDST based image fusion algorithm performance is compared with that of the well-known wavelet based image fusion algorithm. From the results it is observed that the performance of image fusion using MDST is almost similar to that of wavelet based image fusion algorithm. The proposed MDST based image fusion techniques are computationally very simple and it is suitable. The proposed MDST based image fusion algorithms are computationally, exceptionally basic and it is appropriate for real time medical diagnosis applications.

Item Type: Article
Uncontrolled Keywords: Multi resolution; DST; Image processing; Medical image fusion; Fusion quality evaluation metrics
Subjects: AERONAUTICS > Aircraft Communication & Navigation
ENGINEERING > Communications and Radar
Depositing User: Dr VPS Naidu
Date Deposited: 27 Jul 2017 03:40
Last Modified: 27 Jul 2017 03:40

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