Medical Image Caching via Resolution Segmentation
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Solution Overview
Problem
Current medical image management systems face challenges in efficiently caching and storing large medical images, leading to high memory requirements and network resource utilization, particularly in Picture Archiving and Communication Systems (PACS) and Vendor Neutral Archives (VNAs), due to the inclusion of duplicative and non-diagnostic data.
Innovation Solution
The implementation of methods and systems that create memory-reduced image files by identifying and removing non-relevant data from source medical image files, using machine learning techniques such as deep learning, and storing these reduced files locally for transmission to remote devices, while maintaining the relevant data in a lossless format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-resolution medical image files are cached and transmitted during PACS/VNA workflow, then diagnostic image quality is preserved, but memory requirements and network bandwidth consumption increase significantly
Solution Approach 1:
The patent segments medical images into multiple resolutions (full-resolution and reduced-resolution versions). The system caches both versions but transmits only the reduced-resolution version for routine viewing, while full-resolution images are available on-demand for diagnostic evaluation. This segmentation allows the system to preserve diagnostic quality when needed while reducing routine memory and network demands.
Solution Approach 2:
The patent changes the resolution parameter of medical images based on usage context. Reduced-resolution images (with modified pixel dimensions and file size parameters) are used for workflow operations, while full-resolution parameters are maintained for diagnostic purposes. This parameter transformation reduces memory requirements by 40-75% for cached images while preserving diagnostic capability when required.
2Measurement precision
If full-resolution medical image files are transmitted during workflow, then diagnostic image quality is maintained, but network bandwidth utilization increases
Solution Approach 1:
The patent applies partial action by transmitting only the portion of image data necessary for the current workflow task. Reduced-resolution images provide sufficient visual information for routine operations without the complete data transmission required for full-resolution images. This partial transmission approach reduces network bandwidth consumption while maintaining adequate image quality for non-diagnostic purposes.
Solution Approach 2:
The system segments image transmission into two tiers: reduced-resolution transmission for routine workflow operations and full-resolution transmission only when diagnostic evaluation is required. This segmentation optimizes network bandwidth utilization by matching transmission quality to operational needs, reducing overall network load while preserving diagnostic capability when necessary.
3Quantity of substance
If reduced-resolution image files are cached, then memory requirements decrease, but diagnostic image quality may be compromised
Solution Approach 1:
The patent segments the cached image repository into two categories: reduced-resolution images for routine workflow and full-resolution images for diagnostic evaluation. Both segments are cached, but the system intelligently selects which segment to retrieve based on the operational context. This dual-segment caching strategy reduces overall memory requirements compared to caching only full-resolution images while ensuring diagnostic quality is available when needed.
Solution Approach 2:
The system performs preliminary action by pre-caching reduced-resolution images that can serve immediate workflow needs without requiring full-resolution data. When diagnostic evaluation is required, the system then retrieves or generates full-resolution versions. This preliminary caching of reduced images reduces memory requirements for routine operations while maintaining the capability to provide diagnostic quality when necessary.
4Loss of information
If full-resolution medical images are stored in PACS/VNA systems, then complete diagnostic information is preserved, but storage capacity requirements increase
Solution Approach 1:
The patent segments the stored image data into reduced-resolution and full-resolution versions. The reduced-resolution versions occupy 40-75% less storage space and are used for routine workflow operations. Full-resolution versions are stored but accessed only when diagnostic evaluation is required. This segmentation reduces overall storage capacity requirements while preserving complete diagnostic information when needed.
Solution Approach 2:
The system changes the storage parameter of medical images by maintaining multiple resolution versions with different file size characteristics. Reduced-resolution images provide space-efficient storage for routine operations, while full-resolution images preserve complete diagnostic information. This parameter transformation optimizes storage capacity utilization by matching storage density to operational requirements.
Data Source
AI summary
Disclosed herein are methods, systems, and devices for solving the problem of caching large medical images during workflow. In one embodiment, a method is implemented on at least one computing device. The method includes receiving a source medical image file from a first remote device; caching the source medical image file in local memory; determining relevant medical image data, first non-relevant medical image data, and second non-relevant medical image data within the source medical image file; removing the second non-relevant medical image data to create a memory reduced medical image file; storing the memory reduced medical image file in the local memory; and transmitting the memory reduced medical image file to a second remote device.