Server-Based 3D Rendering for Medical Imaging via Parameter Streaming
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Solution Overview
Problem
The increasing volume and complexity of medical imaging data sets, particularly in 3D and 4D CT scans, lead to substantial data transfer times and high computational demands, causing inefficiencies in radiologist workstations and other hospital systems, especially over low-bandwidth networks.
Innovation Solution
Implementing a server-based rendering method where client computers send rendering parameters to a server for image processing, using video compression and adaptive resolution to reduce network load, allowing simultaneous execution of pipeline stages for efficient data transfer and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If volume data is transferred from PACS server to workstation over network, then data becomes available for viewing, but transfer time increases substantially for large datasets
Solution Approach 1:
The patent extracts the rendering function from the client workstation and relocates it to a dedicated render server. Only essential viewing parameters and final rendered images are transferred over the network, while the large volume data remains on the server. This separation allows radiologists to view large datasets without transferring the entire dataset, dramatically reducing network transfer time while maintaining full viewing capability.
Solution Approach 2:
The render server acts as an intermediary between the PACS server and the radiologist's workstation. It receives volume data from PACS, performs rendering operations, and sends back only the rendered images. This intermediary architecture allows the system to handle large datasets efficiently by processing them on the server rather than transferring them entirely to the client.
2Productivity
If workstation is equipped with powerful hardware to process large volume data, then viewing performance improves, but cost and complexity increase
Solution Approach 1:
The patent extracts the computationally intensive rendering function from the client workstation and places it on a dedicated render server. This allows the workstation to remain simple and cost-effective while still achieving high viewing performance through the server's processing power. The workstation only needs to handle lightweight tasks like sending viewing parameters and displaying rendered images.
Solution Approach 2:
The render server provides universal rendering capability that can serve multiple workstations simultaneously. Instead of each workstation needing its own powerful hardware, a single multi-functional render server can handle rendering requests from multiple radiologists, reducing overall system complexity and cost while maintaining high performance for all users.
3Measurement precision
If rendering is performed on viewing computer, then image quality is maintained, but network bandwidth requirements increase significantly
Solution Approach 1:
The patent extracts the rendering process from the client and performs it on the server. The server renders images at full resolution and quality, then transmits only the rendered image data rather than the entire volume dataset. This approach maintains image quality while dramatically reducing network bandwidth requirements compared to transferring raw volume data for client-side rendering.
4Adaptability or versatility
If multiple clients access volume data simultaneously, then system versatility improves, but network load and processing demands increase
Solution Approach 1:
The render server is designed to handle multiple rendering requests simultaneously from different clients. It can process volume data once and serve multiple clients with the same or different viewing parameters, or handle multiple different volume datasets concurrently. This universal rendering capability allows the system to support multiple users with diverse needs while efficiently managing network bandwidth and processing resources.
Solution Approach 2:
The system performs preliminary rendering on the server before clients need the images. By pre-rendering volume data and storing rendered images or rendering parameters on the server, the system can quickly serve multiple clients without requiring them to transfer large datasets or wait for client-side rendering. This preliminary action reduces network load when multiple clients access data simultaneously.
Data Source
AI summary
A method of server site rendering 3D images on a server computer coupled to a client computer wherein the client computer instructs a server computer to load data for 3D rendering and sends a stream of rendering parameter sets to the server computer, each set of rendering parameters corresponding with an image to be rendered; next the render computer renders a stream of images corresponding to the stream of parameter sets and the stream of images is compressed with a video compression scheme and sent from the server computer to the client computer where the client computer decompresses the received compressed video stream and displays the result in a viewing port. The rendering and communication chain is subdivided in successive pipeline stages that work in parallel on successive rendered image information.