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Research progress on lossless compression technology for medical images
LIU Yu  CUI Hao-ran  NIAN Yong-jian  QIU Ming-guo 

DOI:10.12015/issn.1674-8034.2016.02.013.


[Abstract] Medical imaging technique has been the central supported technique for modern clinical medicine diagnosis and treatment. However, for the images obtained by various medical imaging devices, so huge dataset creates heavy burden for image storage and transmission and restricts the following application of medical images. Therefore, it is necessary to exploit efficient compression technique to compress various medical images. Lossless compression can completely keep the total information of original medical images, which has been widely accepted in the practical application. In this paper, the research progress on lossless compression for medical images is summarized and analyzed; finally, its development trend is expected.
[Keywords] Medical image；Lossless compression；Region of interest；Magnetic resonance imaging；Wavelet transform

LIU Yu The Second Squad of the 4-th Platoon, the 19-th Student Battalion, Third Military Medical University, Chongqing 400038, China

CUI Hao-ran The Second Squad of the 5-th Platoon, the 19-th Student Battalion, Third Military Medical University, Chongqing 400038, China

NIAN Yong-jian* Department of Medical Images, School of Biomedical Engineering, Third Military Medical University, Chongqing 400038, China

QIU Ming-guo Department of Medical Images, School of Biomedical Engineering, Third Military Medical University, Chongqing 400038, China

*Correspondence to: Nian YJ, E-mail: yjnian@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of National Natural Science Foundation of China Youth Science Foundation Project No. 41201363
Received  2015-11-30
Accepted  2015-12-28
DOI: 10.12015/issn.1674-8034.2016.02.013
DOI:10.12015/issn.1674-8034.2016.02.013.

[1]
Castiglione A, Pizzolante R, Santis AD, et al. Cloud-based adaptive compression and secure management services for 3D healthcare data. Future Generation Computer Systems, 2015, 43-44: 120-134.
[2]
万建伟, 粘永健, 苏令华, 等. 高光谱图像压缩技术研究进展.信号处理, 2010, 26(9): 1397-1407.
[3]
Weinberger MJ, Seroussi G, Sapiro G. The LOCO-I losslessimage compressionalgorithm: principles and standardization into JPEG-LS. IEEE Transactions on Image Processing, 2000, 9(8): 1309-1324.
[4]
Wu X, Memon ND. Context-based adaptive lossless image coding. IEEE Transactions on Communication, 1997, 45(4): 437-444.
[5]
张晓玲，沈兰荪．一种基于自适应预测的医学图像高效无损压缩方法. 电子学报, 2001, 29(12A): 1914-1916.
[6]
杨玲, 饶妮妮, 杜晓川 等. 基于像素间相关性的医学MRI图像无损压缩方法. 航天医学与医学工程, 2012, 25(3): 202-206.
[7]
Thangavelu K, Krishnan T. Lossless color medical image compression using adaptive block-based encoding for human computed tomographic images. International Journal of Image Systems and Technology, 2013, 23(3): 227-234.
[8]
Puthooran E, Anand RS, Mukherjee S. Lossless compression of medical images using a dual level DPCM with context adaptive switching neural network predictor. International Journal of Computational Intelligence Systems, 2013, 6(6): 1082-1093.
[9]
Rizzo F, Carpentieri B, Motta G, et al. Low-complexity lossless compression of hyperspectral imagery via linear prediction. IEEE Signal Processing Letter, 2005, 12(2): 138-141.
[10]
Liang JY, Chen CS, Huang CH. Lossless compression of medical images using Hilbert space-filling curves. Computerized Medical Imaging and Graphics, 2008, 32(3): 174-182.
[11]
Arif AS, Mansor S, Logeswaran R, et al. Auto-shape lossless compression of pharynx and esophagus fluoroscopic images. Journal of Medical Systems, 2015, 39(2): 1-7.
[12]
Lim CE, Kim GD, Yoon CH, et al. Context modeling based lossless compression of radio-frequency data for software-based ultrasound beamforming. Biomedical Signal Processing and Control, 2013, 8(6): 682-687.
[13]
Pizzolante R, Castiglione A, Carpentieri B, et al. Parallel low-complexity lossless coding of three-dimensional medical images. International Conference on Network-Based Information Systems, Salerno, Italy, 2014: 91-98.
[14]
Philips W, Assche SV, Rycke DD, et al. State-of-the-art techniques for lossless compression of 3D medical image sets. Computerized Medical Imaging and Graphics, 2001, 25(2): 173-185.
[15]
Spelic D, Zalik B. Lossless compression of threshold-segmented medical images. Journal of Medical Systems, 2012, 36(4): 2349-2357.
[16]
Sanchez V, Nasiopoulos P, Abugharbieh R. Efficient lossless compression of 4-D medical images based on the advanced video coding scheme. IEEE Transactions on Information Technology in Biomedicine, 2008, 12(4): 442-445.
[17]
Sanchez V, Bartrina-Rapesta J. Lossless compression of medical images based on HEVC intracoding. IEEE International Conference on Acoustic, Speech and Signal Processing, Florence, Italy, 2013: 6622-6626.
[18]
Miaou SG, Ke FS, Chen SC. A lossless compression method for medical image. IEEE Transactions on Information Technology in Biomedicine, 2009, 13(5): 818-821.
[19]
Karimi N, Samavi S, Amraee S, et al. Use of symmetry in prediction-error field for losslesscompression of 3D MRI images. Multimedia Tools and Applications, 2015, 74(24): 11007-11022.
[20]
Sanchez V, Abugharbieh R, Nasiopoulos P. Symmetry-based scalable lossless compression of 3D medical image data. IEEE Transactions on Medical Imaging, 2009, 28(7): 1062-1072.
[21]
Bairagi VK. Symmetry-based biomedical image compression. Journal of Digital Imaging, 2015, 28(6): 718-726.
[22]
Xiong ZX, Wu XL, Cheng S, et al. Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms. IEEE Transactions on Medical Imaging, 2003, 22(3): 459-470.
[23]
Cho SD, Kim DY, Pearlman WA. Lossless compression of volumetric medical images with improved three-dimensional SPIHT algorithm. Journal of Digital Imaging, 2004, 17(1): 57-63.
[24]
Wu XL, Qiu T. Wavelet coding of volumetric medical images for high throughput and operability. IEEE Transactions on Medical Imaging, 2005, 24(6): 719-727.
[25]
Qi XJ, Tyler JM. A progressive transmission capable diagnostically lossless compression scheme for 3D medical image sets. Information Sciences, 2005, 175(3): 217-243.
[26]
Kassim AA, Yan PK, Lee WS, et al. Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms. IEEE Transactions on Information Technology in Biomedicine, 2005, 9(1): 132-138.
[27]
钟文燕, 杨丰, 陈燕萍. 改进的4D-SPIHT医学图像无损压缩.计算机工程与应用, 2010, 46(32): 147-151.
[28]
Kumar SVB, Nagaraj N, Mukhopadhyay S, et al. Block-based conditional entropy coding for medical image. Proceedings of SPIE, 2003, 5033: 375-381.
[29]
Chen YT, Tseng DC. Wavelet-based medical image compression with adaptive prediction. Computerized Medical Imaging and Graphics, 2007, 31(1): 1-8.
[30]
赵丽红, 田亚男, 沙永刚, 等. DPCM与小波变换结合的医学图像无损压缩. 东北大学学报, 2007, 28(10): 1454-1457.
[31]
Anusuya V, Srinivasa Raghavan V, Kavitha G. Lossless compression on MRI images using SWT. Journal of Digital Imaging, 2014, 27(5): 594-600.
[32]
Venugopal D, Mohan S, Raja S. An efficient block based lossless compression of medical images. International Journal for Light and Electron Optics, 2016, 127(2): 754-758.
[33]
张桂珊, 肖刚, 戴卓智, 等. 压缩感知技术及其在MRI上的应用. 磁共振成像, 2013, 4(4): 314-320.

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