摘要
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.
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.
