A rapid compression technique for 4-D functional MRI images using data rearrangement and modified binary array techniques
Tóm tắt
Compression techniques are vital for efficient storage and fast transfer of medical image data. The existing compression techniques take significant amount of time for performing encoding and decoding and hence the purpose of compression is not fully satisfied. In this paper a rapid 4-D lossy compression method constructed using data rearrangement, wavelet-based contourlet transformation and a modified binary array technique has been proposed for functional magnetic resonance imaging (fMRI) images. In the proposed method, the image slices of fMRI data are rearranged so that the redundant slices form a sequence. The image sequence is then divided into slices and transformed using wavelet-based contourlet transform (WBCT). In WBCT, the high frequency sub-band obtained from wavelet transform is further decomposed into multiple directional sub-bands by directional filter bank to obtain more directional information. The relationship between the coefficients has been changed in WBCT as it has more directions. The differences in parent–child relationships are handled by a repositioning algorithm. The repositioned coefficients are then subjected to quantization. The quantized coefficients are further compressed by modified binary array technique where the most frequently occurring value of a sequence is coded only once. The proposed method has been experimented with fMRI images the results indicated that the processing time of the proposed method is less compared to existing wavelet-based set partitioning in hierarchical trees and set partitioning embedded block coder (SPECK) compression schemes [1]. The proposed method could also yield a better compression performance compared to wavelet-based SPECK coder. The objective results showed that the proposed method could gain good compression ratio in maintaining a peak signal noise ratio value of above 70 for all the experimented sequences. The SSIM value is equal to 1 and the value of CC is greater than 0.9 for all experiments. Subjective evaluation on the reconstructed images indicated that the proposed method could reproduce the diagnostic features of fMRI images clearly.
Tài liệu tham khảo
Pearlman WA, Islam A, Nagaraj N, Said A (2004) Efficient, low-complexity image coding with a set-partitioning embedded block coder. IEEE Trans Circuits Syst Video Technol 14:1219–1235
Rajeswari R, Rajesh R (2009) Efficient compression of 4D fMRI images using bandelet transform and fuzzy thresholding. In: Proceedings of World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), Coimbatore, India
Nguyen BP, Chui CK, Ong SH, Chang S (2011) An efficient compression scheme for 4-D medical images using hierarchical vector quantization and motion compensation. Comput Biol Med 41:843–856
Zeng L, Jansen CP, Marsch S, Unser M, Hunziker PR (2002) Four-dimensional wavelet compression of arbitrarily sized echo cardiographic data. IEEE Trans Med Imaging 21:1179–1187
Lalgudi HG, Bilgin A, Marcellin MW, Tabesh A, Nadar MS, Trouard TP (2005) Four-dimensional compression of fMRI using JPEG 2000. In: Proceedings of SPIE International Symposium on Medical Imaging, San Diego, California
Lalgudi HG, Bilgin A, Marcellin MW, Nadar MS (2005) Compression of fMRI and ultrasound images using 4D SPIHT. In: Proceedings of 2005 IEEE International Conference on Image Processing (ICIP 2005), Genoa, Italy
Kassim AA, Yan P, Lee WS, Sengupta K (2005) Motion compensated lossy-to- lossless compression of 4-D medical images using integer wavelet transforms. IEEE Trans Inf Technol Biomed 9:132–138
Liu Y, Pearlman WA (2007) Four-dimensional wavelet compression of 4-D medical images using scalable 4-DSBHP. In: Proceedings of 2007 Data Compression Conference (DCC’07), Snowbird, Utah
Sanchez V, Nasiopoulos P, Abugharbieh R (2008) Efficient lossless compression of 4-D medical images based on the advanced video coding scheme. IEEE Trans Inf Technol Biomed 12:442–446
Sanchez V, Nasiopoulos P, Abugharbieh R (2009) Novel lossless fMRI image compression based on motion compensation and customized entropy coding. IEEE Trans Inf Technol Biomed 13:645–655
Do MN, Vetterli M (2005) The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans Image Process 14:2091–2106
Eslami R, Radha H (2004)Wavelet-based contourlet transform and its application to image coding. In: Proceedings of IEEE International Conference on Image Processing, MI, USA
Tian X, Zheng X, Ding T (2008) Wavelet- based contourlet coding using speck algorithm. In: Proceedings of international conference on signal processing (ICSP 2008), Beijing, China
Chikouche D, Benzid R, Bentoumi M (2008) Application of the DCT and arithmetic coding to medical image compression. International conference on information and communication technologies: From Theory to Applications (ICTTA 2008), Damascus, Syria. doi: 10.1109/ICTTA.2008.4530107
Uma VetriSelvi G, Nadarajan R (in press) CT and MRI image compression using wavelet based contourlet transform and binary array technique. J Real Time Image Process. doi 10.1007/s11554-014-0400-7
Singh S, Kumar V, Verma HK (2007) Adaptive threshold-based classification in medical image compression for Teleradiology. Comput Biol Med 37:811–819