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DC Field | Value | Language |
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dc.contributor.author | Parmar, Ashish | - |
dc.contributor.author | Kumar, Pardeep [Guided by] | - |
dc.date.accessioned | 2022-08-12T10:23:49Z | - |
dc.date.available | 2022-08-12T10:23:49Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5790 | - |
dc.description.abstract | In this world of evolution, medical technology is evolving day by day and with the more use of medical imaging in clinical practices, digital information is increasing rapidly. So, for the effective storage and transmission of this digital information, there is a need for data compression. In past years, a variety of compression techniques are reported by many researchers for the effective compression of medical images and information. In this work, we presented a review of these compression techniques with the proper classification of these techniques, their performance parameters and their advantages in the field of the medical image compression. After reviewing a variety of papers, selected a mechanism which is the mixture of the region of interest and a combination of transforming techniques for the compression of the medical images. the implementation of the work is simulated in MATLAB environment. It is showed that the presented region of interest-based hybrid technique shows effective and efficient results. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Magnetic resonance imaging | en_US |
dc.subject | Ultrasound | en_US |
dc.subject | Electrocardiogram | en_US |
dc.subject | Electroencephalogram | en_US |
dc.subject | Medical images | en_US |
dc.title | Region of Interest-based Hybrid Compression Technique for Medical Images | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | Dissertations (M.Tech.) |
Files in This Item:
File | Description | Size | Format | |
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Region of Interest-based Hybrid Compression Technique for Medical Images.pdf | 1.45 MB | Adobe PDF | View/Open |
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