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The DICOM Image Compression and Patient Data Integration using Run Length and Huffman Encoder
, Vijay Mankar R
Published in IntechOpen
Pages: 1 - 18

Maintaining human healthcare is one of the biggest challenges that most of the

increasing population in Asian countries are facing today. There is an unrelenting

need in our medical community to develop applications that are low on cost, with

high compression, as huge number of patient’s data and images need to be transmitted

over the network to be reviewed by the physicians for diagnostic purpose. This

implemented work represents discrete wavelet-based threshold approach. Using this

approach by applying N-level decomposition on 2D wavelet types like Biorthogonal,

Haar, Daubechies, Coiflets, Symlets, Reverse Biorthogonal, and Discrete Meyer, var-

ious levels of wavelet coefficients are obtained. The lossless hybrid encoding algo-

rithm, which combines run-length encoder and Huffman encoder, has been used for

compression and decompression purpose. This work is proposed to examine the

efficiency of different wavelet types and to determine the best. The objective of this

research work is to improve compression ratio and compression gain.

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