Incremental Medical Image Compression for Cloud Processing
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Solution Overview
Problem
Current methods for processing medical image data in radiology face bottlenecks due to high transfer times caused by limited bandwidth, which restricts the use of cloud computing resources and is economically disadvantageous, especially when using public networks or data-intensive processing algorithms.
Innovation Solution
The method involves incremental compression of medical image data at the source, transferring it in compressed form to a cloud system, where it is decompressed and processed in multiple units, allowing for efficient processing and result transfer, with the number of compression and decompression levels corresponding to the number of processing units and dynamically adapting to network bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data-intensive processing algorithms are executed locally to avoid network transfer delays, then processing speed is improved, but hardware costs and infrastructure requirements increase significantly
Solution Approach 1:
The patent segments the data processing workflow into distinct phases: local compression of raw data, selective transfer of compressed data to cloud, cloud-based processing of compressed data, and transfer of results back. This segmentation allows each component to operate optimally without requiring full local infrastructure or承受 full network transfer burdens.
Solution Approach 2:
The patent introduces compressed data as an intermediary form between raw data and processed results. By converting raw data into a compressed intermediate representation, the system reduces network transfer volume while maintaining the ability to perform meaningful processing operations in the cloud, thus avoiding both full local processing requirements and direct raw data transfer.
2Ease of manufacture
If public networks are used for cloud data transfer, then infrastructure costs are reduced, but transfer times increase due to limited bandwidth
Solution Approach 1:
The patent applies compression algorithms that transform data from its original format into a compressed representation, fundamentally changing the data's size parameter. This parameter change reduces the volume of data that needs to be transferred over public networks, thereby maintaining cost-effectiveness while significantly reducing transfer times.
3Quantity of substance
If data is compressed using traditional methods before cloud transfer, then transfer bandwidth is reduced, but compression and decompression time delays increase significantly
Solution Approach 1:
The patent applies different compression strategies to different types of medical data based on their specific characteristics and processing requirements. By tailoring the compression approach to the local qualities of each data type, the system achieves efficient compression without uniform time delays across all data processing operations.
Data Source
AI summary
In a method and a system for processing medical image data in a cloud system, image data acquired at a modality are compressed via an incremental compression and transferred in compressed form to a decompressor of the cloud system. The decompressor relays the decompression result to different processing units for incremental processor in order to provide a result that is then relayed to the modality and/or to additional computer-based instances.