TY - JOUR
T1 - Diagnostically lossless coding of X-ray angiography images based on background suppression
AU - Xu, Zhongwei
AU - Bartrina-Rapesta, Joan
AU - Blanes, Ian
AU - Sanchez, Victor
AU - Serra-Sagristà, Joan
AU - García-Bach, Marcel
AU - Francisco Muñoz, Juan
PY - 2016/7/1
Y1 - 2016/7/1
N2 - © 2016 Elsevier Ltd X-ray angiography images are widely used to identify irregularities in the vascular system. Because of their high spatial resolution and the large amount of images generated daily, coding of X-ray angiography images is becoming essential. This paper proposes a diagnostically lossless coding method based on automatic segmentation of the focal area using ray-casting and α-shapes. The diagnostically relevant Region of Interest is first identified by exploiting the inherent symmetrical features of the image. The background is then suppressed and the resulting images are encoded using lossless and progressive lossy-to-lossless methods, including JPEG-LS, JPEG2000, H.264 and HEVC. Experiments on a large set of X-ray angiography images suggest that our method correctly identifies the Region of Interest. When compared to the case of coding with no background suppression, the method achieves average bit-stream reductions of nearly 34% and improvements on the reconstruction quality of up to 20 dB-SNR for progressive decoding.
AB - © 2016 Elsevier Ltd X-ray angiography images are widely used to identify irregularities in the vascular system. Because of their high spatial resolution and the large amount of images generated daily, coding of X-ray angiography images is becoming essential. This paper proposes a diagnostically lossless coding method based on automatic segmentation of the focal area using ray-casting and α-shapes. The diagnostically relevant Region of Interest is first identified by exploiting the inherent symmetrical features of the image. The background is then suppressed and the resulting images are encoded using lossless and progressive lossy-to-lossless methods, including JPEG-LS, JPEG2000, H.264 and HEVC. Experiments on a large set of X-ray angiography images suggest that our method correctly identifies the Region of Interest. When compared to the case of coding with no background suppression, the method achieves average bit-stream reductions of nearly 34% and improvements on the reconstruction quality of up to 20 dB-SNR for progressive decoding.
KW - Alpha-shapes filters
KW - Diagnostically lossless coding
KW - Ray casting segmentation
KW - Region of interest compression
KW - X-ray angiography images
U2 - 10.1016/j.compeleceng.2016.02.014
DO - 10.1016/j.compeleceng.2016.02.014
M3 - Article
SN - 0045-7906
VL - 53
SP - 319
EP - 332
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
ER -