ABSTRACT
In this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.
Subject(s)
Algorithms , Computer Security , Data Compression/methods , Image Interpretation, Computer-Assisted/methods , Signal Processing, Computer-Assisted , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
This pictorial review provides the principles of extracorporeal membrane oxygenation (ECMO) support and associated CT imaging features with emphasis on the hemodynamic changes and possible imaging pitfalls encountered. It is important that radiologists in ECMO centers apply well-designed imaging protocols and familiarize themselves with post-contrast CT imaging findings in patients on ECMO.
