DPU Medical Imaging Transfer With Low-Latency DICOM Offload
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Solution Overview
Problem
Medical imaging data protocols like DICOM cause increased latencies due to data traveling through all OSI layers and encryption/decryption at the application layer, leading to slower data processing and security vulnerabilities, especially in healthcare settings where real-time processing is critical.
Innovation Solution
Utilizing data processing units (DPUs) to perform encryption, decryption, compression, and decompression at a lower layer, bypassing the kernel layer and reducing CPU load, thereby accelerating data transfer and processing without modifying the DICOM protocol.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data encryption and compression are performed at the application layer using current medical imaging data protocols, then data security and data reduction are achieved, but latency increases and processing speed decreases
Solution Approach 1:
The patent moves data encryption and compression operations from the application layer to the data plane of the network stack, creating a new dimensional approach to data processing. This allows security functions to execute in parallel with data transmission rather than sequentially, reducing latency while maintaining security.
Solution Approach 2:
The patent introduces a intermediary data plane processing layer between the application layer and the network transport layer. This intermediary handles encryption and compression operations, acting as a mediator that prevents these time-consuming operations from blocking the main data transmission path in the application layer.
2Reliability
If medical imaging data is transmitted through all OSI layers and processed by medical imaging data applications, then protocol compliance and data integrity are maintained, but processing latency increases
Solution Approach 1:
The patent segments the data processing workflow into distinct functional planes: control plane for protocol management and data integrity verification, and data plane for high-speed data transmission and preprocessing operations. This segmentation allows parallel processing of different data aspects simultaneously.
Solution Approach 2:
The patent performs preliminary data compression and encryption in the data plane before data reaches the application layer. By preparing data in advance in the faster data plane, the application layer receives pre-processed data ready for immediate use, improving overall processing speed without compromising integrity.
3Adaptability or versatility
If the medical imaging data protocol is widely adopted, then interoperability and compatibility are improved, but the ability to update and optimize the protocol decreases
Solution Approach 1:
The patent creates a universal data plane processing layer that works with multiple medical imaging protocols simultaneously. This layer provides protocol-agnostic data encryption, compression, and acceleration functions that can serve DICOM and other protocols, allowing protocol updates without affecting the core data processing infrastructure.
Solution Approach 2:
The patent implements a virtualized data plane processing environment that can replicate and test protocol updates in isolated copies before deploying to production. This allows protocol evolution through copying and testing mechanisms without disrupting existing interoperable systems.
4Measurement precision
If more images are acquired with thinner slices in MRI and CT scans, then imaging precision and diagnostic quality are improved, but data storage requirements and processing load increase
Solution Approach 1:
The patent dynamically changes data representation parameters through real-time compression in the data plane. By adjusting compression ratios and data formats based on imaging modality and diagnostic requirements, the system maintains high imaging precision while reducing the quantity of stored and transmitted data.
Solution Approach 2:
The patent replaces traditional mechanical storage and processing approaches with software-defined data plane processing. This substitution enables efficient data reduction through algorithmic compression and selective data plane operations, managing large volumes of high-precision imaging data without proportional increases in physical storage requirements.
Data Source
AI summary
A system includes a data processing unit (DPU). The DPU is to receive one or more packets for medical imaging data, the one or more packets having a first format that conforms to a medical imaging data protocol. The DPU is to process the one or more packets into one or more updated packets having a second format that does not conform to the medical imaging data protocol and transmit the one or more updated packets to a target device configured to receive packets having the first format that conforms to the medical data protocol.