Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bae KT, Whiting BR. CT data storage reduction by means of compressing projection data instead of images: feasibility study. Radiology. 2001;219(3):850–855.
Brennecke R, et al. American College of Cardiology/European Society of Cardiology international study of angiographic data compression phase III. Measurement of image quality differences at varying levels of data compression. Eur Heart J. 2000;21(8):687–696.
Chan H, et al. Image compression in digital mammography: effects on computerized detection of subtle microcalcifications. Med Phys. 1996;23(8):1325–1336.
Good W, Maitz G, Gur D. Joint photographic experts group (JPEG) compatible data compression of mammograms. J Digit Imaging. 1994;7(3):123–132.
Erickson BJ, et al. Requirements for an enterprise digital image archive. J Digit Imaging. 2001;14(2):72–82.
Hangiandreou NJ, et al. The effects of irreversible JPEG compression on an automated algorithm for measuring carotid artery intima-media thickness from ultrasound images. J Digit Imaging. 2002;15(suppl 1):258–260.
Huang H. Progress in image processing technology related to radiological sciences: a five-year review. Comput Methods Programs Biomed. 1987;25(2):143–156.
Kerensky RA, et al. American College of Cardiology/European Society of Cardiology international study of angiographic data compression phase I. The effects of lossy data compression on recognition of diagnostic features in digital coronary angiography. Eur Heart J. 2000;21(8):668–678.
Ko JP, et al. Wavelet compression of low-dose chest CT data: effect on lung nodule detection. Radiology. 2003;228(1):70–75.
Kotter E, et al. Evaluation of lossy data compression of chest X-rays: a receiver operating characteristic study. Invest Radiol. 2003;38(5):243–249.
Li F, et al. Effects of JPEG and wavelet compression of spiral low-dose CT images on detection of small lung cancers. Acta Radiol. 2001;42(2):156–160.
Manduca A, et al. Histogram transformation for improved compression of CT images. In Medical Imaging 1997. Newport Beach, CA: SPIE; 1997.
Manduca A, et al. 3-D compression of medical images with Set Partitioning in Hierarchical Trees. In RSNA. Chicago: RSNA; 1997.
Megibow AJ, et al. Computed tomography diagnosis utilizing compressed image data: an ROC analysis using acute appendicitis as a model. J Digit Imaging. 2002;15(2):84–90.
Ohgiya Y, et al. Acute cerebral infarction: effect of JPEG compression on detection at CT. Radiology. 2003;227(1):124–127.
Persons KR, et al. Evaluation of irreversible JPEG compression for a clinical ultrasound practice. J Digit Imaging. 2002;15(1):15–21.
Ritenour ER. Lossy compression should not be used in certain imaging applications such as chest radiography. For the proposition. Med Phys. 1999;26(9):1773–1774.
Said A, Pearlman W. A new fast and efficient codec based on set partitioning in hierarchical trees. IEEE Trans Trans Circuits and Systems for Video Technology. 1996;6:243–250.
Savcenko V, et al. Detection of subtle abnormalities on chest radiographs after irreversible compression. Radiology. 1998;206(3):609–616.
Siddiqui K, et al. Improved image compression at various slice thicknesses for multislice CT using 3-D JPEG2000 (part 2) in comparison with conventional 2-D compression. In Soc Computer Applications in Radiology. Vancouver, BC: SCAR; 2004.
Slone RM, Muka E, Pilgram TK. Irreversible JPEG compression of digital chest radiographs for primary interpretation: assessment of visually lossless threshold. Radiology. 2003;228(2):425–429.
Sung MM, et al. Clinical evaluation of compression ratios using JPEG2000 on computed radiography chest images. J Digit Imaging. 2002;15(2):78–83.
Suryanarayanan S, et al. A perceptual evaluation of JPEG 2000 image compression for digital mammography: contrast-detail characteristics. J Digit Imaging. 2004;17(1):64–70.
Tuinenburg JC, et al. American College of Cardiology/European Society of Cardiology international study of angiographic data compression phase II. The effects of varying JPEG data compression levels on the quantitative assessment of the degree of stenosis in digital coronary angiography. Eur Heart J. 2000;21(8):679–686.
Yamamoto S, et al. Evaluation of compressed lung CT image quality using quantitative analysis. Radiat Med. 2001;19(6):321–329.
Zhang Y, Pham B, Eckstein M. Automated optimization of JPEG 2000 encoder options based on model observer performance for detecting variable signals in X-ray coronary angiograms. IEEE Trans Med Imaging. 2004;23(4):459–474.
Zheng B, et al. Applying computer-assisted detection schemes to digitized mammograms after JPEG data compression: an assessment. Acad Radiol. 2000;7(8):595–602.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Science+Business Media, Inc.
About this chapter
Cite this chapter
Erickson, B.J. (2006). Image Compression. In: Dreyer, K.J., Thrall, J.H., Hirschorn, D.S., Mehta, A. (eds) PACS. Springer, New York, NY. https://doi.org/10.1007/0-387-31070-3_12
Download citation
DOI: https://doi.org/10.1007/0-387-31070-3_12
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-26010-5
Online ISBN: 978-0-387-31070-1
eBook Packages: MedicineMedicine (R0)