The quest for 'diagnostically lossless' medical image compression: a comparative study of objective quality metrics for compressed medical images

Ilona Kowalik-Urbaniak; Dominique Brunet; Jiheng Wang; David Koff; Nadine Smolarski-Koff; Edward R. Vrscay; Bill Wallace; Zhou Wang

doi:10.1117/12.2043196

11 March 2014 The quest for 'diagnostically lossless' medical image compression: a comparative study of objective quality metrics for compressed medical images

Ilona Kowalik-Urbaniak, Dominique Brunet, Jiheng Wang, David Koff, Nadine Smolarski-Koff, Edward R. Vrscay, Bill Wallace, Zhou Wang

Author Affiliations +

Proceedings Volume 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment; 903717 (2014) https://doi.org/10.1117/12.2043196
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Our study, involving a collaboration with radiologists (DK,NSK) as well as a leading international developer of medical imaging software (AGFA), is primarily concerned with improved methods of assessing the diagnostic quality of compressed medical images and the investigation of compression artifacts resulting from JPEG and JPEG2000. In this work, we compare the performances of the Structural Similarity quality measure (SSIM), MSE/PSNR, compression ratio CR and JPEG quality factor Q, based on experimental data collected in two experiments involving radiologists. An ROC and Kolmogorov-Smirnov analysis indicates that compression ratio is not always a good indicator of visual quality. Moreover, SSIM demonstrates the best performance, i.e., it provides the closest match to the radiologists' assessments. We also show that a weighted Youden index¹ and curve tting method can provide SSIM and MSE thresholds for acceptable compression ratios.

Citation Download Citation

Ilona Kowalik-Urbaniak, Dominique Brunet, Jiheng Wang, David Koff, Nadine Smolarski-Koff, Edward R. Vrscay, Bill Wallace, and Zhou Wang "The quest for 'diagnostically lossless' medical image compression: a comparative study of objective quality metrics for compressed medical images", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 903717 (11 March 2014); https://doi.org/10.1117/12.2043196

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