AI-Guided Medical Image Compression for Diagnostic Integrity
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Solution Overview
Problem
Medical images compressed using lossy compression techniques often result in reduced image quality, making them less useful for diagnostic purposes, as they can lose critical information necessary for accurate medical diagnoses.
Innovation Solution
A method involving artificial intelligence (AI) diagnostic tests is employed to compress medical images while maintaining diagnostic quality by identifying the highest compression ratio that preserves image integrity, using a combination of lossless and lossy compression techniques to store images without reducing their medical usefulness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression is used to reduce file size, then storage efficiency is improved, but image quality is degraded
Solution Approach 1:
The system applies multiple compression algorithms with different compression ratios (parameters) to the same medical image. By varying the compression parameter and evaluating diagnostic quality at each level, the system identifies the optimal compression ratio that achieves maximum file size reduction while preserving sufficient diagnostic information.
Solution Approach 2:
The system performs AI-based diagnostic evaluation as feedback on compressed images to determine whether diagnostic quality is maintained. This feedback mechanism allows the system to iteratively select compression levels, keeping the highest compression ratio that still produces diagnostically acceptable images.
2Volume of stationary object
If higher compression ratio is applied, then storage space is reduced, but diagnostic value is lost
Solution Approach 1:
The system systematically varies the compression ratio parameter across multiple levels and evaluates diagnostic reliability at each level using AI algorithms. This allows identification of the compression parameter threshold where diagnostic value is preserved while storage space is maximally reduced.
Solution Approach 2:
The system generates multiple compressed versions of medical images at different compression ratios. These compressed images serve as disposable alternatives to the original high-quality images, allowing storage of lower-quality versions that still maintain diagnostic adequacy, thereby reducing overall storage requirements.
Data Source
AI summary
Method for storing a compressed digital image includes performing an artificial intelligence (“AI”) diagnostic test on the digital image; determining an uncompressed diagnostic result associated with the digital image based on the AI diagnostic test; generating one or more compressed digital images by compressing the digital image, each compressed digital image having a respective compression ratio; decompressing each compressed digital image to generate a respective decompressed digital image; performing the diagnostic test on each decompressed digital image; determining a decompressed diagnostic result associated with each decompressed digital image based on the respective diagnostic test; identifying one or more decompressed digital images having a respective decompressed diagnostic result that is the same as the uncompressed diagnostic result; selecting from the identified one or more decompressed digital images, the decompressed digital image associated with the highest compression ratio; and storing the compressed digital image associated with the selected decompressed digital image.