CT Detector Data Compression Using Lossy-Lossless Staging
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Solution Overview
Problem
Modern computed tomography systems face challenges in efficiently compressing and transmitting massive multi-dimensional data while minimizing information loss, as lossy compression limits achievable ratios and lossless compression is slow and insufficient.
Innovation Solution
A two-stage data compression scheme is implemented, using lossy compression followed by lossless compression, leveraging noise levels and photon distribution to optimize efficiency and then employing entropy coding methods like ANS for further compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If lossy compression is used to increase compression ratio, then bandwidth and storage requirements are reduced, but information loss increases
Solution Approach 1:
The compression process is divided into two distinct stages: first a lossy compression stage that achieves significant compression ratio, followed by a lossless compression stage that recovers information. This segmentation allows the system to benefit from both high compression ratios and minimal information loss by combining the strengths of both approaches.
Solution Approach 2:
The patent applies parameter changes by adjusting the precision of detector data through controlled rounding or truncation in the lossy stage, then fully recovering these parameters in the lossless stage. This allows flexible control over the balance between compression ratio and information preservation depending on the specific application requirements.
2Productivity
If lossless compression is used to minimize information loss, then data accuracy is maintained, but processing speed decreases
Solution Approach 1:
The compression process is divided into two distinct stages: first a lossy compression stage that achieves significant compression ratio, followed by a lossless compression stage that recovers information. This segmentation allows the system to benefit from both high compression ratios and minimal information loss by combining the strengths of both approaches.
Solution Approach 2:
The lossy compression stage performs a partial compression action that removes only the least significant information, while the subsequent lossless stage completes the compression without further information loss. This partial action approach allows the majority of compression to occur in the faster lossy stage.
3Quantity of substance
If higher compression ratio is achieved, then bandwidth requirements are reduced, but data transmission time may increase due to complex processing
Solution Approach 1:
The compression process is divided into two distinct stages: first a lossy compression stage that achieves significant compression ratio, followed by a lossless compression stage that recovers information. This segmentation allows the system to benefit from both high compression ratios and minimal information loss by combining the strengths of both approaches.
Solution Approach 2:
The lossy compression stage performs a partial compression action that removes only the least significant information, while the subsequent lossless stage completes the compression without further information loss. This partial action approach allows the majority of compression to occur in the faster lossy stage.
Data Source
Figure 1~2
Figure 3~5
Figure 6
AI summary
For compressing data of a computed tomography, CT, system (1), detector data (5) is received from an X-ray detector of the CT system (1), pre-compressed data (6) is generated by compressing the detector data (5) using a lossy compression method, and fully compressed data (7) is generated depending on the pre-compressed data (6) using a lossless compression method.