Diagnostically lossless coding of X-ray angiography images based on background suppression

Zhongwei Xu, Joan Bartrina-Rapesta, Ian Blanes, Victor Sanchez, Joan Serra-Sagristà, Marcel García-Bach, Juan Francisco Muñoz

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)

Abstract

© 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.
Original languageEnglish
Pages (from-to)319-332
JournalComputers and Electrical Engineering
Volume53
DOIs
Publication statusPublished - 1 Jul 2016

Keywords

  • Alpha-shapes filters
  • Diagnostically lossless coding
  • Ray casting segmentation
  • Region of interest compression
  • X-ray angiography images

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