Diagnostically lossless compression of X-ray angiography images based on automatic segmentation using ray-casting and α-shapes
2013
X-ray angiography (angio) images are widely used to identify irregularities in the vascular system. Because of their high spatial resolution and the increasing amount of X-ray angio images generated, compression of these images is becoming paramount. In this paper, we propose a diagnostically lossless compression method based on automatic segmentation using ray-casting and α-shapes. The diagnostically relevant Region of Interest is separated from the background by exploiting the inherent symmetrical features of the image. The background-suppressed images are then losslessly encoded using DICOM-compliant lossless compression methods. Experimental results suggest that the proposed method correctly identifies the Region of Interest in X-ray angio images with an average segmentation accuracy of 98.4% and achieves more than 2 bits per pixel improvement on compression performance as compared to lossless compression with no background suppression.
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