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Lossless ROI Medical Image Coding Methods Based on SPIHT


Affiliations
1 Department of Electrical Engineering, IIT Roorkee, Roorkee-247667, India
     

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In telemedicine or medical imaging applications very small part of the image is of diagnostic importance. So, bycompressing the region of interest (ROI) in loss less manner and the unimportant background data in a lossy manner we can save data size and hence transmission time. The SPIHT was designed for optimal progressive transmission i.e., at any point during the decoding, the quality of the displayed image is the best that can be achieved for the number of bits input by the decoder up to that moment. So, if ROI feature is added to SPIHT very high compression ratios can be achieved. In this paper different possible ways for adding Region-of-Interest (ROI) coding functionality to SPIHT are discussed and the results are compared with MAXSHIFT algorithm.


Keywords

Maxshift, ROI, Medical Image Compression, SPIHT.
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  • Lossless ROI Medical Image Coding Methods Based on SPIHT

Abstract Views: 191  |  PDF Views: 1

Authors

Tirupathiraju Kanumuri
Department of Electrical Engineering, IIT Roorkee, Roorkee-247667, India
M. L. Dewal
Department of Electrical Engineering, IIT Roorkee, Roorkee-247667, India
R. S. Anand
Department of Electrical Engineering, IIT Roorkee, Roorkee-247667, India

Abstract


In telemedicine or medical imaging applications very small part of the image is of diagnostic importance. So, bycompressing the region of interest (ROI) in loss less manner and the unimportant background data in a lossy manner we can save data size and hence transmission time. The SPIHT was designed for optimal progressive transmission i.e., at any point during the decoding, the quality of the displayed image is the best that can be achieved for the number of bits input by the decoder up to that moment. So, if ROI feature is added to SPIHT very high compression ratios can be achieved. In this paper different possible ways for adding Region-of-Interest (ROI) coding functionality to SPIHT are discussed and the results are compared with MAXSHIFT algorithm.


Keywords


Maxshift, ROI, Medical Image Compression, SPIHT.