Open Access
Diagnostic Quality Evaluation of Compressed Medical Images for Telemedicine Applications
TLDR
The evaluation of diagnostic quality of compressed medical images using objective and subjective testing will be presented and the quality of the reconstructed images has been measured objectively using objective measures such as MSE, MAE, SNR, and PSNR.Abstract:
Many techniques for achieving data compression have been introduced. The fundamental goal of image data compression is to reduce the bit rate for transmission or storage while maintaining an acceptable reproduction quality, but it is natural to raise the question of how much an image can be compressed and still preserve sufficient information for a given telemedicine application. Evaluation of the quality of compressed medical image for telemedicine applications still remains an important issue. In this paper, the evaluation of diagnostic quality of compressed medical images using objective and subjective testing will be presented. Three different medical image modalities which are CT, MRI, and X-ray have been compressed and decompressed using DWT for different compression ratios. The quality of the reconstructed images has been measured objectively using objective measures such as MSE, MAE, SNR, and PSNR. Ten non specialist observers have been involved to carry out the subjective evaluation. Based on the quality of the reconstructed images, the PSNR obtained has been between 35.3dB to 58.0dB for CT scan images, 38.6dB to 55.0dB for MRI and 34.5dB to 51.0dB for x-ray images. For clinical applications such as telemedicine or teleradiology, the compression ratio of 30:1 is acceptable for CT images, and a compression ratio of 40:1 is acceptable for MRI, and compression ratio of 20:1 is acceptable for x-ray images.read more
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References
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Image quality measures and their performance
A.M. Eskicioglu,P.S. Fisher +1 more
TL;DR: Although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques, and a graphical measure called Hosaka plots can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.
Evaluating quality of compressed medical images : SNR, subjective rating, and diagnostic accuracy : Data compression
TL;DR: Three approaches to the measurement of medical image quality are described: signal-to-noise ratio (SNR), subjective rating, and diagnostic accuracy, which compare and contrast in a particular application, and recently developed methods for determining diagnostic accuracy of lossy compressed medical images are considered.
Journal ArticleDOI
Evaluating quality of compressed medical images: SNR, subjective rating, and diagnostic accuracy
TL;DR: In this paper, the authors describe three approaches to the measurement of medical image quality: signal-to-noise ratio (SNR), subjective rating, and diagnostic accuracy, and consider in some depth recently developed methods for determining diagnostic accuracy of lossy compressed medical images and examine how good the easily obtainable distortion measures like SNR are at predicting the more expensive subjective and diagnostic ratings.
Journal ArticleDOI
Irreversible Compression of Medical Images
TL;DR: This paper describes the technology and artifacts commonly used in irreversible compression of medical images, routinely applied in teleradiology, and often in Picture Archiving and Communications Systems.