Title :
Diagnostically lossless compression of X-ray angiography images based on automatic segmentation using ray-casting and α-shapes
Author :
Zhongwei Xu ; Bartrina-Rapesta, J. ; Sanchez, Victor ; Serra-Sagrista, J. ; Munoz-Gomez, J.
Author_Institution :
Dept. of Inf. & Commun. Eng., Univ. Autonoma de Barcelona, Barcelona, Spain
Abstract :
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.
Keywords :
diagnostic radiography; image coding; image resolution; image segmentation; medical image processing; α-shapes; DICOM-compliant lossless compression; X-ray angiography image; automatic segmentation; background-suppressed image; diagnostically lossless compression; image compression; ray-casting; region-of-interest; spatial resolution; symmetrical features; vascular system; Accuracy; Image coding; Image segmentation; Medical diagnostic imaging; Transform coding; X-ray imaging; X-ray angiography images; alpha-shapes; diagnostically lossless compression; ray casting;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738152