79
Views
0
CrossRef citations to date
0
Altmetric
Articles

An Approach for Diagnostically Lossless Coding of Volumetric Medical Data Based on Wavelet and Just-Noticeable-Distortion Model

ORCID Icon, ORCID Icon & ORCID Icon

References

  • A. Nosratinia, N. Mohsenian, M. Orchard, and B. Liu, “Interframe coding of magnetic resonance images,” IEEE Trans. Med. Imaging, Vol. 15, no. 5, pp. 639–647, 1996. doi: 10.1109/42.538941
  • A. Klappenecker, F. May, and T. Beth, “Lossless compression of 3D MRI and CT data,” Proc. SPIE Int. Soc. Opt. Eng., Vol. 3458, pp. 140–149, 1998.
  • W. Dajun, and T. Chon. “Lossless medical image compression algorithm exploring three-dimensional space,” WCC 2000-ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress, Vol. 2, pp. 1062–1064, IEEE, 2000.
  • A. Bilgin, G. Zweig, and M. W. Marcellin. “Efficient lossless coding of medical image volumes using reversible integer wavelet transforms,” Proceedings DCC’98 Data Compression Conference, pp. 428–437, IEEE, 1998.
  • G. Menegaz, and J. Thiran, “Lossy to lossless object-based coding of 3-D MRI data,” IEEE Trans. Image Process., Vol. 11, no. 9, pp. 1053–1061, 2002. doi: 10.1109/TIP.2002.802525
  • G. Menegaz, and J. Thiran, “Three-dimensional encoding/two-dimensional decoding of medical data,” IEEE Trans. Med. Imaging, Vol. 22, no. 3, pp. 424–440, 2003. doi: 10.1109/TMI.2003.809689
  • Z. Xiong, X. Wu, S. Cheng, and J. Hua, “Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms,” IEEE Trans. Med. Imaging, Vol. 22, no. 3, pp. 459–470, 2003. doi: 10.1109/TMI.2003.809585
  • P. E. Sophia, and J. Anitha, “A hybrid contextual compression technique using wavelet and contourlet transforms with PSO optimized prediction,” Int. J. Imaging Syst. Technol., Vol. 27, no. 2, pp. 171–181, 2017. doi: 10.1002/ima.22221
  • A. F. Guarda, J. M. Santos, L. A. da Silva Cruz, P. A. Assuncao, N. M. Rodrigues, and S. M. de Faria, “A method to improve HEVC lossless coding of volumetric medical images,” Signal Process., Image Commun., Vol. 59, pp. 96–104, 2017. doi: 10.1016/j.image.2017.02.002
  • Z. Zuo, X. Lan, L. Deng, S. Yao, and X. Wang, “An improved medical image compression technique with lossless region of interest,” Optik. (Stuttg), Vol. 126, no. 21, pp. 2825–2831, 2015. doi: 10.1016/j.ijleo.2015.07.005
  • M. Kaur, and V. Wasson, “ROI based medical image compression for telemedicine application,” Procedia. Comput. Sci., Vol. 70, pp. 579–585, 2015. doi: 10.1016/j.procs.2015.10.037
  • H. Hamout, and A. Elyousfi. “Low complexity intra mode decision algorithm for 3D-HEVC,” 25th European Signal Processing Conference (EUSIPCO), pp. 1475–1479, IEEE, 2017.
  • D. Yee, S. Soltaninejad, D. Hazarika, G. Mbuyi, R. Barnwal, and A. Basu. “Medical image compression based on region of interest using better portable graphics (BPG),” IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 216–221, IEEE, 2017.
  • V. Sanchez, R. Abugharbieh, and P. Nasiopoulos, “3-D scalable medical image compression with optimized volume of interest coding,” IEEE Trans. Med. Imaging, Vol. 29, no. 10, pp. 1808–1820, 2010. doi: 10.1109/TMI.2010.2052628
  • J. Taquet, and C. Labit, “Hierarchical oriented predictions for resolution scalable lossless and near-lossless compression of CT and MRI biomedical images,” IEEE Trans. Image Process., Vol. 21, no. 5, pp. 2641–2652, 2012. doi: 10.1109/TIP.2012.2186147
  • V. Sanchez, and J. Bartrina-Rapesta. “Lossless compr ession of medical images based on HEVC intra coding,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6622–6626, IEEE, 2014.
  • T. Bruylants, A. Munteanu, and P. Schelkens, “Wavelet based volumetric medical image compression,” Signal Process., Image Commun., Vol. 31, pp. 112–133, 2015. doi: 10.1016/j.image.2014.12.007
  • D. Wu, D. Tan, M. Baird, J. DeCampo, C. White, and H. Wu, “Perceptually lossless medical image coding,” IEEE Trans. Med. Imaging, Vol. 25, no. 3, pp. 335–344, 2006. doi: 10.1109/TMI.2006.870483
  • Z. Liu, L. J. Karam, and A. B. Watson, “JPEG2000 encoding with perceptual distortion control,” IEEE Trans. Image Process., Vol. 15, no. 7, pp. 1763–1778, 2006. doi: 10.1109/TIP.2006.873460
  • C. Xu, and J. L. Prince, “Snakes, shapes, and gradient vector flow,” IEEE Trans. Image Process., Vol. 7, no. 3, pp. 359–369, 1998. doi: 10.1109/83.661186
  • K. Fukunaga. Introduction to statistical pattern recognition. Amsterdam: Elsevier, 2013.
  • G. K. Wallace, “The JPEG still picture compression standar,” IEEE Trans. Consum. Electron., Vol. 38, no. 1, pp. 18–34, 1992. doi: 10.1109/30.125072
  • H. R. Sheikh, and A. C. Bovik. “Image information and visual quality,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 3, pp. 430–444, IEEE, 2004.
  • Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process., Vol. 13, no. 4, pp. 600–612, 2004. doi: 10.1109/TIP.2003.819861
  • M. Razaak, M. G. Martini, and K. Savino, “A study on quality assessment for medical ultrasound video compressed via HEVC,” IEEE. J. Biomed. Health. Inform., Vol. 18, no. 5, pp. 1552–1559, 2014. doi: 10.1109/JBHI.2014.2326891
  • I. A. Kowalik-Urbaniak, J. Castelli, N. Hemmati, D. Koff, N. Smolarski-Koff, E. R. Vrscay, J. Wang, and Z. Wang, “Modelling of subjective radiological assessments with objective image quality measures of brain and body CT images,” International Conference Image Analysis and Recognition, pp. 3–13, Springer, Cham, 2015.
  • D. M. Chandler, and S. S. Hemami, “VSNR: A wavelet-based visual signal-to-noise ratio for natural images,” IEEE Trans. Image Process., Vol. 16, no. 9, pp. 2284–2298, 2007. doi: 10.1109/TIP.2007.901820
  • I. Kowalik-Urbaniak, D. Brunet, J. Wang, D. Koff, N. Smolarski-Koff, E. R. Vrscay, B. Wallace, and Z. Wang, “The quest for diagnostically lossless medical image compression: a comparative study of objective quality metrics for compressed medical image,” International Society for Optics and Photonics, Vol. 9037, pp. 903717–903717, 2014.
  • A. B. Watson, G. Y. Yang, J. Solomon, and J. Villasenor, “Visibility of wavelet quantization nois,” IEEE Trans. Image Process., Vol. 6, no. 8, pp. 1164–1175, 1997. doi: 10.1109/83.605413
  • HP-LABS. LOCO-1/JPEG-LS: JPEG-LS reference encoder - V.1.00, http://www.hpl.hp.com/loco, (Accessed on January 2019).
  • OPEN-JPEG. Openjpeg, open source c-libary for jpeg 2000, https://code.google.com/p/openjpeg/wiki/Downloads?tm-=2, (Accessed on January 2019).
  • OPEN-JPEG-3D. Openjpeg, open source C-library for JPEG 3D, https://code.google.com/p/openjpeg/downloads/detail?name=openjpeg3d_v1_3.tar.gz&can=4&q=, (Accessed on January 2019).
  • R. Pizzolante, and B. Carpentieri. “Lossless, low-complexity, compression of three-dimensional volumetric medical images via linear prediction,” 18th International Conference on Digital Signal Processing (DSP), pp. 1–6, IEEE, 2013.
  • KAKADU, KAKADU Version 7.4 JPEG2000 software development tool kit, http://kakadusoftware.com/, (Acce-ssed on January 2019).
  • B. K. Chandrika, P. Aparna, and S. Sumam David. “Irreversible wavelet compression of radiological images based on visual threshold,” IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE, 2015.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.