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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Multimodal Medical Image Fusion Techniques |
| Authors Name: | Yogeshwaran R , Geetha G |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_211768
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| Published Paper Id: | IJNRD2401035 |
| Published In: | Volume 9 Issue 1, January-2024 |
| DOI: | |
| Abstract: | Multi-modal medical image fusion may be a well-known area of picture fusion research. Image fusion is the technique of creating one image from the pertinent data from several images taken of the same scene. The resulting merged image is more comprehensive and useful than any of the input images. Diagnostic accuracy depends on imaging technology. Medical image fusion research has gained popularity since the little information offered by single mode medical images cannot satisfy the demand for clinical diagnosis, which necessitates a substantial amount of information. Single-mode fusion and multimodal fusion are subcategories of medical picture fusion. The advantages and disadvantages of each medical technique, such as X-rays, CT scans, MRIs, nuclear medicine, and others, used to check the body's organs, vary. Then, a Non Subsampled Contourlet Transform (NSCT)-based fusion algorithm is used to fuse the Magnetic Resonance Imaging (MRI) and computed tomography (CT) scan images. Additionally, In order to improve the viability of denoising algorithms, In this research, a novel one-stage blind real picture method is proposed, using a modular architecture to denoising network RIDNet. A residual on the residual structure is used by us to Facilitate the flow of low-frequency data and use feature attention to take advantage of channel dependencies In order to increase the robustness, Denoising Convolutional Neural Network (DnCNN) is utilized. |
| Keywords: | Medical images, Multimodal fusion, Security, image denoising, nonsubsampled contourlet transform, RID Net, High and Low frequency ,Deep convolutional neural network. |
| Cite Article: | "Multimodal Medical Image Fusion Techniques", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 1, page no.a318-a323, January-2024, Available :http://www.ijnrd.org/papers/IJNRD2401035.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2401035 Registration ID: 211768 Published In: Volume 9 Issue 1, January-2024 DOI (Digital Object Identifier): Page No: a318-a323 Country: chennai, Tamilnadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2401035 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2401035 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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