#26: Three dimensional wavelet coding of magnetic resonance images


J. Vass, J. Yao, K. Palaniappan, and X. Zhuang

IASTED Computer Graphics and Imaging, pgs. 128--133, 1999

image compression, image analysis, video coding, biomedical

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Abstract

Three-dimensional significance-linked connected component analysis (3D-SLCCA) is pro- posed for compression of volumetric magnetic reso- nance imaging (MRI) data. Due to relatively low inter-slice correlation and high noise level of MRI, 3D- SLCCA treats two MRI slices as a processing unit. By using the Haar wavelet, the temporal lowpass and temporal highpass subbands are obtained as the sum and difference of two consecutive slices, respectively. Then dyadic spatial wavelet decomposition is applied on each temporal subband separately, and significant wavelet coefficients are organized and represented by using the SLCCA technique. The proposed 3D-SLCCA codec provides high compression efficiency, progressive volume representation, low complexity, and transmis- sion error resilience. These desirable features make 3D- SLCCA especially well suited for use within a clinical picture archiving and communication system (PACS) and telemedicine.