Paper
26 May 1999 Testing observer's ability to detect if an image was compressed shows large observer variability
Celine Huguenin, Virginie Chameroy, Florent Aubry, Irene Buvat, Habib Benali, Andrew Todd-Pokropek, Robert Di Paola
Author Affiliations +
Abstract
In medical imaging, many methods of irreversible compression have been studied. However, none of them has been adopted as a standard, probably because of the lack of agreement regarding what is meant by 'acceptable' for an irreversible compression scheme. Among the numerous evaluation studies which have been performed, few only involved a psychovisual approach, and it is unsafe to draw definite conclusion from the reported result. The purpose of this work was to determine the importance of intra and inter observer variability in the psychovisual evaluation of irreversible compression methods for a very specific evaluation protocol involving digitized images of breast parenchyma and imags simulating breast parenchyma using a fractal model. the compression methods to be evaluated were JPEG and Embedded Zerotree Wavelet. Six radiologists had to determine whether each image had been compressed and decompressed. ROC analysis was performed to characterize the performance in compression detection. The large intra and inter observer variability observed in the detection of compression underlines the difficulty of determining an 'acceptable' scheme of irreversible compression in medical imaging in general, and bring the approval of irreversible compression schemes into question.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Celine Huguenin, Virginie Chameroy, Florent Aubry, Irene Buvat, Habib Benali, Andrew Todd-Pokropek, and Robert Di Paola "Testing observer's ability to detect if an image was compressed shows large observer variability", Proc. SPIE 3658, Medical Imaging 1999: Image Display, (26 May 1999); https://doi.org/10.1117/12.349466
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CITATIONS
Cited by 2 patents.
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KEYWORDS
Image compression

Databases

Medical imaging

Mammography

Computer simulations

Fractal analysis

Image quality

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