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Lossless Compression of Medical Images Using 3-D Predictors

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Resumo(s)

Thispaper describes a highly efficientmethod for lossless compression of volumetric sets of medical images, such as CTs or MRIs. The proposed method, referred to as 3-D-MRP, is based on the principle ofminimum rate predictors (MRPs), which is one of the state-of-the-art lossless compression technologies presented in the data compression literature. The main features of the proposed method include the use of 3-D predictors, 3-D-block octree partitioning and classification, volume-based optimization, and support for 16-b-depth images. Experimental results demonstrate the efficiency of the 3-D-MRP algorithm for the compression of volumetric sets of medical images, achieving gains above 15% and 12% for 8- and 16-bitdepth contents, respectively, when compared with JPEGLS, JPEG2000, CALIC, and HEVC, aswell as other proposals based on the MRP algorithm.

Descrição

Palavras-chave

Minimum rate predictors 3D predictors lossless compression medical image compression volumetric data compression

Contexto Educativo

Citação

L. F. R. Lucas, N. M. M. Rodrigues, L. A. da Silva Cruz and S. M. M. de Faria, "Lossless Compression of Medical Images Using 3-D Predictors," in IEEE Transactions on Medical Imaging, vol. 36, no. 11, pp. 2250-2260, Nov. 2017, doi: 10.1109/TMI.2017.2714640

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Fascículo

Editora

Institute of Electrical and Electronics Engineers (IEEE)

Licença CC

Sem licença CC

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