Adaptive Compression for Medical Measurement Data
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Solution Overview
Problem
Existing methods for compressing measurement data from measurement volumes, particularly in medical engineering and computer tomography, face challenges in achieving high compression rates without corrupting relevant data, especially in applications like inline workpiece testing where large datasets are generated, and there is a need for improved traceability and storage efficiency.
Innovation Solution
A computer-implemented method that uses an evaluation rule to define regions of interest within a measurement volume, applying different compression rates and methods to ensure high-quality data in critical areas while allowing higher compression in less critical regions, thereby optimizing storage and bandwidth usage without corrupting relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If measurement data are compressed with high compression rates, then storage requirements are reduced, but the measurement data are corrupted
Solution Approach 1:
The patent applies different compression rates to different regions of the measurement data based on their relevance. Regions marked by the user as relevant are compressed losslessly or with only minor losses, while greater losses are accepted in remaining regions. This local differentiation allows high overall compression rates while preserving data integrity in critical areas.
Solution Approach 2:
The measurement data are divided into multiple regions with differing relevance. The system segments the data space and applies region-specific compression strategies, allowing different parts of the dataset to be treated differently based on their importance for analysis and traceability.
2Reliability
If lossless compression is applied to all regions, then data integrity is maintained, but compression rate remains low
Solution Approach 1:
The patent implements locally adaptive compression where relevant regions receive lossless or minor-loss compression while other regions accept higher losses. This approach achieves high overall compression rates while maintaining data integrity where needed for analysis and traceability.
Solution Approach 2:
The measurement data are segmented into regions of differing relevance, allowing the system to apply appropriate compression strategies to each segment. This segmentation enables high compression rates in non-critical regions while preserving integrity in analysis-relevant regions.
3Quantity of substance
If regions with no detected defects are strongly compressed, then storage efficiency is improved, but traceability of analysis results cannot be reliably provided
Solution Approach 1:
The system performs a preliminary analysis to identify regions containing defects or regions of interest before applying compression. Based on this preliminary evaluation, it determines which regions require preservation for traceability and applies appropriate compression strategies accordingly, ensuring that traceability is maintained in critical regions while achieving storage efficiency elsewhere.
Data Source
AI summary
Described is a method for compressing measurement data of a volume which comprises an object, wherein a digital representation of the object comprising a plurality of image information items of the object is generated by the measurement. The method comprises: providing an analysis specification for at least one predetermined region in the measurement volume; determining the measurement data in the measurement volume; defining a subset of the measurement data which corresponds to the at least one predetermined region of the analysis specification; selecting at least one compression rate for the subset on the basis of the analysis specification; selecting a first compression method for a remainder of the measurement data outside the subset, the first compression method having a compression rate; compressing the subset with the selected at least one compression rate, and compressing the remainder of the measurement data by way of the first compression method.