Compression of mammograms for medical practice

This paper considers effective compression methods for mammogram storing and interchange. A controversy problem of irreversible compression of medical images is studied in clinical tests to check usefulness and possibility of acceptance of wavelet-based compression for clinical applications. Diagnostic accuracy is measured in abnormality detection tests with ROC-based analysis, and by subjective rating of diagnostically important image features affecting lesion symptoms and image ordering according to preserved diagnostic accuracy. The efficiency of the most approved lossless coders is compared to efficiency of irreversible wavelet coding in acceptable rate range. General conclusion is that more effective irreversible compression of mammograms up to 1bpp is safe (i.e. preserves diagnostic accuracy), according to opinions of radiologists participating the experiments and presented results.

[1]  Bernd Meyer,et al.  TMW - a new method for lossless image compression , 1997 .

[2]  W F Good,et al.  Detection of masses and clustered microcalcifications on data compressed mammograms: an observer performance study. , 2000, AJR. American journal of roentgenology.

[3]  J Kivijärvi,et al.  A Comparison of Lossless Compression Methods for Medical Images , 2022 .

[4]  M.J. Weinberger,et al.  Lossless compression of continuous-tone images , 2000, Proceedings of the IEEE.

[5]  Pamela C. Cosman,et al.  Image quality in lossy compressed digital mammograms , 1997, Signal Process..

[6]  Artur Przelaskowski Detail Preserving Wavelet-Based Compression with Adaptive Context-Based Quantisation , 1998, Fundam. Informaticae.

[7]  Y H Chang,et al.  Applying computer-assisted detection schemes to digitized mammograms after JPEG data compression: an assessment. , 2000, Academic radiology.

[8]  David A. Clunie,et al.  Lossless compression of grayscale medical images: effectiveness of traditional and state-of-the-art approaches , 2000, Medical Imaging.

[9]  Pamela C. Cosman,et al.  Evaluating quality of compressed medical images: SNR, subjective rating, and diagnostic accuracy , 1994, Proc. IEEE.

[10]  Artur Przelaskowski Lossless encoding of medical images: Hybrid modification of statistical modeling-based conception , 2001, J. Electronic Imaging.

[11]  Bradley James Erickson,et al.  Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice , 2002, Journal of Digital Imaging.