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Multiresolution Lossy-to-Lossless Coding of MRI Objects

机译:MRI对象的多分辨率无损编码

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摘要

This paper proposes an object-based, highly scalable, lossy-to-lossless coding approach for magnetic resonance (MR) images. The proposed approach, called OBHS-SPIHT, is based on the well known set partitioning in hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. It progressively encodes each slice of the MR data set separately in a multiresolu-tion fashion from low resolution to full resolution and in each resolution from low quality to lossless quality. To achieve more compression efficiency, the algorithm only encodes the main object of interest in the input data set, and ignores the unnecessary background. The experimental results show the efficiency of the proposed algorithm for multiresolution lossy-to-lossless MRI data coding. OBHS-SPIHT, is a very attractive coding approach for medical image information archiving and transmission applications especially over heterogeneous networks.
机译:本文提出了一种基于对象的,高度可扩展的,有损无损的磁共振(MR)图像编码方法。所提出的称为OBHS-SPIHT的方法基于众所周知的层次树中的集划分(SPIHT)算法,并支持质量和分辨率可伸缩性。它以从低分辨率到全分辨率的多分辨率方式以及从低质量到无损质量的每个分辨率,分别对MR数据集的每个切片进行渐进编码。为了获得更高的压缩效率,该算法仅对输入数据集中的主要对象进行编码,而忽略了不必要的背景。实验结果表明,该算法对多分辨率有损无损MRI数据编码的有效性。 OBHS-SPIHT是一种非常有吸引力的编码方法,适用于医学图像信息的归档和传输应用,尤其是在异构网络上。

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