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Visually lossless threshold determination for microcalcification detection in wavelet compressed mammograms

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Abstract.

The aim of this study was to determine the visually lossless threshold of a wavelet-based compression algorithm in case of microcalcification cluster detection in mammography. The threshold was determined by means of observer performance using a set of digitized mammograms. In addition, the transfer characteristics of the compression algorithm were assessed by means of image-quality parameters using computer-generated test images. The observer performance study was based on rating performed by four independent radiologists, who reviewed 68 mammograms, from the Digital Database for Screening Mammography (DDSM), at six different compression ratios. Receiver operating characteristics (ROC) analysis was performed on observers' responses and the area under ROC curve (Az) was calculated at each compression ratio for each observer. The parameters used for assessment of transfer characteristics of the compression algorithm were input/output response, noise, high-contrast response, and low-contrast-detail response. The computer-generated test image, used for this assessment, mimicked mammographic image characteristics (pixel size, pixel depth, and noise) as well as microcalcification characteristics (size and contrast). The ROC analysis for microcalcification cluster detection indicated a threshold at compression ratio 40:1, as Student's t-test shows statistically significant differences in Az values (p<0.05) for compression ratios 70:1 and 100:1. Observers' grading of mammogram quality lowers this threshold at 25:1. Low-contrast-detail detectability in the transfer characteristics study indicate a threshold of 35:1, whereas non-perceptibility of image-quality-parameters degradation lowers this threshold to 30:1. The ROC and transfer characteristics analysis provided comparable thresholds, indicating the potential use of the latter in limiting the target range of compression ratios for subsequent observer studies.

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Acknowledgements. The authors acknowledge Pegasus Imaging Corporation (Tampa, Florida) for permission to use their wavelet-based compression algorithm as an example in this study. O. Kocsis was supported by a grant by the State Scholarship Foundation (SSF), Greece. The authors thank the staff of the Department of Radiology at the University Hospital of Patras for their contribution to this work.

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Authors and Affiliations

  1. Department of Medical Physics, School of Medicine, University of Patras, 26500 , Patras, Greece

    O. Kocsis, L. Costaridou, S. Skiadopoulos & G. Panayiotakis

  2. Department of Radiology, School of Medicine, University of Patras, 26500 , Patras, Greece

    L. Varaki, E. Likaki & C. Kalogeropoulou

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  1. O. Kocsis
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  2. L. Costaridou
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  3. L. Varaki
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  4. E. Likaki
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  5. C. Kalogeropoulou
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  6. S. Skiadopoulos
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  7. G. Panayiotakis
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Correspondence to G. Panayiotakis.

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Kocsis, O., Costaridou, L., Varaki, L. et al. Visually lossless threshold determination for microcalcification detection in wavelet compressed mammograms. Eur Radiol 13, 2390–2396 (2003). https://doi.org/10.1007/s00330-003-1826-7

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