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Publication Type : Conference Paper
Publisher : Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016, Presses Polytechniques Et Universitaires Romandes.
Source : Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016, Presses Polytechniques Et Universitaires Romandes, p.1326-1329 (2016)
ISBN : 9781467393379
Keywords : Anatomical information, Clinical diagnosis, Computerized tomography, Diagnosis, Functional information, Image fusion, Magnetic Resonance Imaging, Medical imaging, Multi modality image, Multi-modal, positron emission tomography, Positron emission tomography (PET), Signal processing, Spectral information, Structural information, Wireless telecommunication systems
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2016
Abstract : Medical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET) etc have been developed and widely used for clinical diagnosis. In brain medical imaging, MRI image shows structural information of the brain without any functional data, where as PET image describes functional information of the brain but with low spatial resolution and so on. These multi-modality images contain important information for the accurate and effective diagnosis of brain diseases. Thus, fusing various modalities of images in medical field into a distinct image with more detailed anatomical information and high spectral information is highly desired in clinical diagnosis. This work presents a detailed literature review done on image fusion and also the concepts and materials that helps for clear understanding of various fusion techniques. © 2016 IEEE.
Cite this Research Publication : Bhavana V. and Krishnappa, H. Kb, “A survey on multi - Modality medical image fusion”, in Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016, 2016, pp. 1326-1329.