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Joan, B.R., Joan, S.S. and Francesc, A. (2009) JPEG2000 ROI Coding Method with Perfect Fine-Grain Accuracy and Lossless Recovery. Proceedings of the 43rd Asilomar Conference on Signals, Systems and Computers. Monterey, California, IEEE Signal Processing Society, USA, 558-562.

has been cited by the following article:

• TITLE: An Algorithm for Medical Imagining Compression That Is Oriented to ROI-Characteristics Protection

  AUTHORS: Renjun Shuai, Yang Shen, Jing Pan

  KEYWORDS: Medical Imaging Compression, ROI Characteristics Protecting, Segmentation, Chain Coding, Shearlet

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.3 No.7, July 15, 2015

  ABSTRACT: In order to protect the ROI (region of interest) characteristics while greatly improving medical imaging compression ratio, we are proposing an algorithm for medical imagining compression that is oriented to ROI-characteristics protection. Firstly, an improved ROI segmentation algorithm is put forward based on the analysis of the ROI segmentation. Then, after the ROI segmented, the ROI edge is extracted and encoded with Freeman chain coding. Finally, the ROI is compressed by lossless compression with shearlet; the ROB (region of background) is compressed by the method of high ratio lossy compression combining with Wavelet and Fractal. Simulation results show that the ROI is segmented precisely. It holds edge integrity and has high quality reconstruction processed by the presented method, helping protect ROI characteristics while greatly improving the compression ratio.