基于运动补偿和定制熵编码的新型无损功能磁共振成像（fMRI）图像压缩

Novel lossless FMRI image compression based on motion compensation and customized entropy coding.

作者信息

Sanchez Victor, Nasiopoulos Panos, Abugharbieh Rafeef

机构信息

Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.

出版信息

IEEE Trans Inf Technol Biomed. 2009 Jul;13(4):645-55. doi: 10.1109/TITB.2009.2021159. Epub 2009 Apr 28.

DOI:10.1109/TITB.2009.2021159

PMID:19403369

Abstract

We recently proposed a method for lossless compression of 4-D medical images based on the advanced video coding standard (H.264/AVC). In this paper, we present two major contributions that enhance our previous work for compression of functional MRI (fMRI) data: 1) a new multiframe motion compensation process that employs 4-D search, variable-size block matching, and bidirectional prediction; and 2) a new context-based adaptive binary arithmetic coder designed for lossless compression of the residual and motion vector data. We validate our method on real fMRI sequences of various resolutions and compare the performance to two state-of-the-art methods: 4D-JPEG2000 and H.264/AVC. Quantitative results demonstrate that our proposed technique significantly outperforms current state of the art with an average compression ratio improvement of 13%.

摘要

我们最近提出了一种基于先进视频编码标准（H.264/AVC）的4D医学图像无损压缩方法。在本文中，我们展示了两项主要成果，它们改进了我们之前对功能磁共振成像（fMRI）数据的压缩工作：1）一种新的多帧运动补偿过程，该过程采用4D搜索、可变大小块匹配和双向预测；2）一种为残差和运动矢量数据的无损压缩设计的新型基于上下文的自适应二进制算术编码器。我们在各种分辨率的真实fMRI序列上验证了我们的方法，并将性能与两种最先进的方法进行比较：4D-JPEG2000和H.264/AVC。定量结果表明，我们提出的技术显著优于当前的技术水平，平均压缩率提高了13%。