Distributed Medical Image Processing Resource Allocation
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Solution Overview
Problem
Existing distributed network systems face inefficiencies in processing medical image data due to the inability to efficiently allocate resources between clients and servers, particularly in low bandwidth networks, and the impracticality of decomposing medical images into constituent parts for distributed imaging.
Innovation Solution
A method and system for medical image processing on a distributed network that involves monitoring system resources and bandwidth to recommend the allocation of resources for processing 3D image data into 2D data, using techniques like multi-planar reformatting, minimum/maximum intensity projection, and volume rendering, with configuration control allowing user adjustment and override of recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If medical images are processed locally on client devices, then processing speed is improved, but device complexity and processing power requirements increase
Solution Approach 1:
The patent segments image processing tasks into different categories (basic processing vs. complex processing) and distributes them between client and server based on complexity. Simple tasks like viewing and basic navigation are performed locally on the client, while complex tasks such as 3D rendering, multi-planar reformatting, and advanced image manipulation are offloaded to the server, thus resolving the contradiction between processing speed and device complexity
Solution Approach 2:
The patent introduces a server as an intermediary between the client and the image data storage. The server handles computationally intensive processing tasks and returns processed images or image data to the client for display. This intermediary approach allows clients with limited processing power to access high-performance processing capabilities without requiring complex local hardware
2Adaptability or versatility
If 3D image data is transmitted to client for processing, then processing flexibility is improved, but network bandwidth requirements increase
Solution Approach 1:
The patent extracts only the necessary 3D image data and processing instructions from the server to the client, rather than transmitting complete image datasets. The system transmits compressed 3D data formats (such as NIfTI, DICOM 3D, or other volumetric data formats) that can be efficiently processed locally, reducing the quantity of data transmitted over the network while maintaining processing flexibility
Solution Approach 2:
The patent performs preliminary processing of 3D image data on the server before transmission to the client. Pre-processing tasks include compression, format conversion, and pre-computed rendering of specific planes or volumes. This preliminary action reduces the amount of data that needs to be transmitted and processed in real-time at the client, thereby reducing bandwidth requirements
3Productivity
If resource allocation is dynamically adjusted based on system monitoring, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors available resources (CPU capacity, memory, network bandwidth, storage availability) on both client and server. Based on this feedback, the system dynamically adjusts the allocation of processing tasks between client and server. The allocation algorithm considers factors such as current system load, network conditions, and task requirements to optimize processing efficiency in real-time
Solution Approach 2:
The patent makes the resource allocation strategy dynamic rather than static. The system can switch between different allocation modes (client-side processing, server-side processing, or hybrid) based on real-time conditions. The allocation is adjusted dynamically in response to changing network conditions, system load, and user requirements, allowing the system to adapt to varying processing needs without requiring complex fixed infrastructure
Data Source
AI summary
Certain embodiments of the present invention provide a method of medical image processing on a distributed network including: communicating on a distributed network comprising a server, a client, and a communications pathway having a bandwidth, wherein the distributed network comprises system resources related to the server, the client, and the communications pathway; monitoring the system resources and the bandwidth with at least one process monitor to generate monitor data; and recommending an allocation of at least a portion of the system resources for processing three dimensional image data to form two dimensional image data displayable on the client, wherein the allocation is based at least in part on the monitor data.