
Proceedings Paper
Real-time compression of raw computed tomography data: technology, architecture, and benefitsFormat | Member Price | Non-Member Price |
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Paper Abstract
Compression of computed tomography (CT) projection samples reduces slip ring and disk drive costs. A lowcomplexity,
CT-optimized compression algorithm called Prism CTTM achieves at least 1.59:1 and up to 2.75:1 lossless
compression on twenty-six CT projection data sets. We compare the lossless compression performance of Prism CT to
alternative lossless coders, including Lempel-Ziv, Golomb-Rice, and Huffman coders using representative CT data sets.
Prism CT provides the best mean lossless compression ratio of 1.95:1 on the representative data set. Prism CT
compression can be integrated into existing slip rings using a single FPGA. Prism CT decompression operates at 100
Msamp/sec using one core of a dual-core Xeon CPU. We describe a methodology to evaluate the effects of lossy
compression on image quality to achieve even higher compression ratios. We conclude that lossless compression of raw
CT signals provides significant cost savings and performance improvements for slip rings and disk drive subsystems in
all CT machines. Lossy compression should be considered in future CT data acquisition subsystems because it provides
even more system benefits above lossless compression while achieving transparent diagnostic image quality. This result
is demonstrated on a limited dataset using appropriately selected compression ratios and an experienced radiologist.
Paper Details
Date Published: 13 March 2009
PDF: 11 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72582H (13 March 2009); doi: 10.1117/12.810599
Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)
PDF: 11 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72582H (13 March 2009); doi: 10.1117/12.810599
Show Author Affiliations
Albert Wegener, Samplify Systems (United States)
Naveen Chandra, GE Healthcare (United States)
Yi Ling, Samplify Systems (United States)
Naveen Chandra, GE Healthcare (United States)
Yi Ling, Samplify Systems (United States)
Robert Senzig, GE Healthcare (United States)
Robert Herfkens, Stanford Univ. School of Medicine (United States)
Robert Herfkens, Stanford Univ. School of Medicine (United States)
Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)
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