Data compression of X-ray cardio-angiographic image series

Abstract

Medical x-ray images are increasingly stored and transmitted in a digital format. To reduce the required storage space and transmission bandwidth, data compression can be applied. In this paper we describe a new method for data compression of cardio-angiographic x-ray image series. The method is based on so-called overlapped-transform coding. A comparison with the well-known block-based transform-coding methods JPEG and MPEG is presented. We found that overlapped-transform coding does not introduce any blocking artefacts, in contrast to block-based transform coding, which introduces clearly visible blocking artefacts at compression ratios above 8. Clinical evaluations of the new method have pointed out that the image quality obtained at a compression ratio of 12 is adequate for diagnostic applications.

A data compression method for image time series

“…Unfortunately, this approach is not acceptable for functional neuroimaging, as it does not properly handle changes in head position during the scan series. Finally, it is worth noting that publicly available lossy compression systems such as MPEG and JPEG are unsuitable for quantitative statistical analyses as commonly performed for functional imaging studies [Breeuwer et al, 1995].…”

An Efficient Low Complexity Lossless Coding Algorithm for Medical Images

“…They concluded that no statistically significant loss of diagnostic quality was detected for 8 or 7-bit compress images with average compression ratios of 16:1 and 28:1 [11] . In 1995, Breeuwer et al [12] discussed the diagnostic consequences of compression using cosine transform. They reported that acceptable compression ratio for image size of 2048, 1024 and 512 pixels were 25:1, 20:1 and 10:1 respectively based on a mean square error of 0.02%.…”

“…They reported that acceptable compression ratio for image size of 2048, 1024 and 512 pixels were 25:1, 20:1 and 10:1 respectively based on a mean square error of 0.02%. The researchers concluded that reconstructed images from compressed image data with a compression ratio of 4:1-16:1 did not result in excessive visual degradation and therefore this technique was suitable for compression of diagnostic images [12] . In 1997, Erickson et al [13] found that a lossy compression of 40:1 or more could be used without perceptible loss in the representation of anatomical structures.…”