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Data Compression and Its Application in Medical Imaging

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Book cover Hybrid and Advanced Compression Techniques for Medical Images

Abstract

With the recent developments in sensors, communications and image acquisition methods, limited data storage, the need of medical image compression is on rising. The data compression plays a vital role in medical imaging science. The data compression provides the compression to each pixel of medical images without changes in actual information. This chapter presents an overview of image compression methods, types of compression methods, and its need in medical imaging science.

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References

  1. Gonzalez, R. C., & Woods, R. E. (2002). Digital image processing (pp. 409–492). Upper Saddle River: Pearson-Prentice-Hall.

    Google Scholar 

  2. Uthayakumar, J., Vengattaraman, T., & Dhavachelvan, P. (2018). A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications. Journal of King Saud University-Computer and Information Sciences, 1–22.

    Google Scholar 

  3. Drost, G. W., & Bourbakis, N. G. (2001). A hybrid system for real-time lossless image compression. Microprocessors and Microsystems, 25(1), 19–31.

    Article  Google Scholar 

  4. Zhang, Y., & Li, J. (2007). Linear predictor-based lossless compression of vibration sensor data: Systems approach. Journal of Engineering Mechanics, 133(4), 431–441.

    Article  Google Scholar 

  5. Sayood, K. (2017). Introduction to data compression. Morgan Kaufmann, USA.

    Google Scholar 

  6. Duszak, R. (2012). Medical imaging: Is the growth boom over. Neiman Report, Harvey L. Reston: Neiman Health Policy Institute.

    Google Scholar 

  7. Van Aken, I. W., Reijns, G. L., De Valk, J. P. J., & Nijhof, J. A. M. (1987, January). Compressed medical images and enhanced fault detection within an ARC-NEMA Compatidle picture archiving and communications system. In Medical imaging (Vol. 767, pp. 290–298). International Society for Optics and Photonics.

    Google Scholar 

  8. Thanki, R., & Borra, S. (2018). Medical imaging and its security in telemedicine applications. Springer, Germany.

    Google Scholar 

  9. MedPix™ Medical Image Database available at: http://rad.usuhs.mil/medpix/medpix.html, https://medpix.nlm.nih.gov/home. Last Access Month: September, 2018.

  10. Cavaro-Ménard, C., Naït-Ali, A., Tanguy, J. Y., Angelini, E., Le Bozec, C., & Le Jeune, J. J. (2008). Specificities of physiological signals and medical images. In Compression of Biomedical Images and Signals (pp. 43–76), USA.

    Google Scholar 

  11. Warnock, M. J., Toland, C., Evans, D., Wallace, B., & Nagy, P. (2007). Benefits of using the DCM4CHE DICOM archive. Journal of Digital Imaging, 20(1), 125–129.

    Article  Google Scholar 

  12. Sahu, B. K., & Verma, R. (2011, April). DICOM search in medical image archive solution e-Sushrut Chhavi. In Electronics computer technology (ICECT), 2011 3rd international conference on (Vol. 6, pp. 256–260). IEEE.

    Google Scholar 

  13. Chen, H., & Jain, A. K. (2005, January). Dental biometrics: Alignment and matching of dental radiographs. In Application of computer vision, 2005. WACV/MOTIONS'05 volume 1. Seventh IEEE workshops on (Vol. 1, pp. 316–321). IEEE.

    Google Scholar 

  14. DICOM PS3.1 2018d. 201. Available online: http://dicom.nema.org/MEDICAL/Dicom/current/output/chtml/part01/PS3.1.html. Last Accessed Month: November 2018.

  15. JTC1 Committee. (1990). Digital compression and coding of continuous-tone still images. Int. Org. Standardization ISO/IEC, JTC1 Committee Draft, JPEG, 8-R8.

    Google Scholar 

  16. Pennebaker, W. B., & Mitchell, J. L. (1992). JPEG: Still image data compression standard. Springer Science & Business Media, Germany.

    Google Scholar 

  17. Boliek, M. (2002). JPEG 2000 image coding system: Core coding system. ISO/IEC. Geneva: ISO.

    Google Scholar 

  18. JPEG 2000. (2011). JPEG 2000 image coding system: Extensions for three-dimensional data. ISO/IEC IS 15444-10. Geneva: ISO.

    Google Scholar 

  19. JPEGLS. (1999). Lossless and near-lossless compression of continuous-tone still images—baseline. ISO/IEC IS 14495-1. Geneva: ISO.

    Google Scholar 

  20. JPIP. (2005). JPEG 2000 image coding system: Interactivity tools, APIs and protocols. ISO/IEC IS 15444-9. Geneva: ISO.

    Google Scholar 

  21. MPEG. (2000). Information technology—generic coding of moving pictures and associated audio information: Systems. ISO/IEC IS 13818-1. Geneva: ISO.

    Google Scholar 

  22. H. 264 (2003). Information technology—coding of audio-visual objects—part 10: Advanced video coding. ISO/IEC IS 14496-10. Geneva: ISO.

    Google Scholar 

  23. European Society of Radiology (ESR). (2011). Usability of irreversible image compression in radiological imaging. A position paper by the European Society of Radiology (ESR).

    Google Scholar 

  24. American College of Radiology. (2016). ACR-AAPM-SIIM technical standard for electronic practice of medical imaging.

    Google Scholar 

  25. Guidance for the Submission of Premarket Notifications for Medical Image Management Devices (2000). Weblink: https://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm073721.pdf. Last Access Month: Nov 2018.

  26. Wong, S., Zaremba, L., Gooden, D., & Huang, H. K. (1995). Radiologic image compression-a review. Proceedings of the IEEE, 83(2), 194–219.

    Article  Google Scholar 

  27. Gooden, D. S. (1993, August). Legal aspects of image compression. In Proceedings of the American Association of Physicists in Medicine (AAPM) 35th Annual meeting (pp. 8–12). Washington, DC.

    Google Scholar 

  28. Bak, P. R. (2006). Will the use of irreversible compression become a standard of practice? Scar News, 18(1), 10.

    Google Scholar 

  29. The Adoption of Lossy Image Data Compression for the Purpose of Clinical Interpretation (2008). Weblink: https://www.rcr.ac.uk/system/files/publication/field_publication_files/IT_guidance_LossyApr08_0.pdf. Last Access Month: November 2018.

  30. CAR Standards for Irreversible Compression in Digital Diagnostic Imaging within Radiology (2011). Weblink: https://car.ca/wp-content/uploads/Compression-in-Digital-Imaging-2011.pdf. Last Access Moth: November 2018.

  31. Loose, R., Braunschweig, R., Kotter, E., Mildenberger, P., Simmler, R., & Wucherer, M. (2009). Compression of digital images in radiology-results of a consensus conference. RoFo: Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin, 181(1), 32–37.

    Article  Google Scholar 

  32. European Society of Radiology (ESR). (2011). Usability of irreversible image compression in radiological imaging. A position paper by the European Society of Radiology (ESR). Insights into Imaging, 2(2), 103–115.

    Article  Google Scholar 

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Thanki, R.M., Kothari, A. (2019). Data Compression and Its Application in Medical Imaging. In: Hybrid and Advanced Compression Techniques for Medical Images. Springer, Cham. https://doi.org/10.1007/978-3-030-12575-2_1

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  • DOI: https://doi.org/10.1007/978-3-030-12575-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12574-5

  • Online ISBN: 978-3-030-12575-2

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