Abstract
New MRI techniques enable the reconstruction of multidimensional data sets, including 3D volumes of cardiac image data reconstructed along both cardiac and respiratory phases. However, these new type of data present several challenges in their manipulation, visualization and analysis, and there are no off-the-shelf tools for the interactive visualization of such high-dimensional data sets. Such a tool, in order to be successful, must deal with large amounts of data, producing animations with no lagging and allowing users to interact in real-time with the volumes. Therefore, one must use efficient lossless compression techniques in order to keep the information while allowing the tool to manipulate the data efficiently. In this work, we report on the development of VisHeart, a multi-platform open source tool for the visualization and analysis of multidimensional cardiac data. The experiments reported here culminated in a file format composed of a combination of standard compression techniques, allowing for the compression of the test dataset with a rate of 2.954 in approximately 6 min, while keeping the decompression time to approximately 15 s for a dataset formed by 52 volumes with \(192 \times 192 \times 192\) voxels. After the initial decompression, the dataset can be visualized in real-time.
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References
Axel, L., Phan, T.S., Metaxas, D.N.: Visualization and analysis of multidimensional cardiovascular magnetic resonance imaging: challenges and opportunities. Front. Cardiovasc. Med. 9, 919810 (2022). https://doi.org/10.3389/fcvm.2022.919810
Deutsch, P.: Deflate compressed data format specification version 1.3 (1996). https://tools.ietf.org/html/rfc1951. Internet Request for Comments (RFC) 1951. Accessed 09 Feb 2023
Farrugia, R.A.: Reversible visible watermarking for H.264/AVC encoded video. In: 2011 IEEE EUROCON - International Conference on Computer as a Tool, pp. 1–4 (2011). https://doi.org/10.1109/EUROCON.2011.5929031
Feng, L., et al.: 5D whole-heart sparse MRI. Magn. Reson. Med. 79(2), 826–838 (2018). https://doi.org/10.1002/mrm.26745
Gailly, J., Adler, M.: Zlib compressed data format specification version 3.3 (1996). https://tools.ietf.org/html/rfc1950. Internet Request for Comments (RFC) 1950. Accessed 09 Feb 2023
van der Geest, R.J., Garg, P.: Advanced analysis techniques for intra-cardiac flow evaluation from 4D flow MRI. Curr. Radiol. Rep. 4(7), 1–10 (2016). https://doi.org/10.1007/s40134-016-0167-7
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 4th edn. Pearson, New York (2017)
Huffman, D.A.: A method for the construction of minimum-redundancy codes. Proc. IRE 40(9), 1098–1101 (1952). https://doi.org/10.1109/JRPROC.1952.273898
Le Gall, D., Tabatabai, A.: Sub-band coding of digital images using symmetric short kernel filters and arithmetic coding techniques. In: ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, vol. 2, pp. 761–764 (1988). https://doi.org/10.1109/ICASSP.1988.196696
Pulavskyi, A., Krivenko, S., Kryvenko, L.S.: Determination of the signal-to-noise ratio for noisy electrocardiogram using lossless data compression. In: 2019 8th Mediterranean Conference on Embedded Computing (MECO), pp. 1–4 (2019). https://doi.org/10.1109/MECO.2019.8760294
Richardson, I.E.G.: H.264 and MPEG-4 Video Compression: Video Coding for Next-Generation Multimedia. Wiley, Hoboken (2003)
Schroeder, W., Martin, K., Lorensen, B.: The Visualization Toolkit: An Object-Oriented Approach to 3D Graphics, 4.1 edn. Kitware Inc, New York (2018)
Schulz, O.: Blitzwave C++ wavelet library. https://oschulz.github.io/blitzwave/. Accessed 10 Feb 2023
Ziv, J., Lempel, A.: A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory 23(3), 337–343 (1977). https://doi.org/10.1109/TIT.1977.1055714
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We would like to thank Mathias Stuber for making the data available for our use.
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Coutinho, E.A.G., Carvalho, B.M., Santos, S.R.d., Axel, L. (2023). VisHeart: A Visualization and Analysis Tool for Multidimensional Data. In: Bernard, O., Clarysse, P., Duchateau, N., Ohayon, J., Viallon, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2023. Lecture Notes in Computer Science, vol 13958. Springer, Cham. https://doi.org/10.1007/978-3-031-35302-4_42
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