Medical Image Preprocessing and Caching for Display Acceleration
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Solution Overview
Problem
In medical applications, the existing client-server architecture for processing and displaying large medical images is resource-intensive and time-consuming, requiring frequent data transfer between client and server for image adjustments, which hampers rapid image display and increases network load.
Innovation Solution
Assigning mandatory and optional attributes to medical images, such as unique identifiers, viewport characteristics, and processing algorithms, allows for preprocessing and caching of images on the server, enabling efficient display on the client with reduced data transfer and improved resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If frequent data transfer between client and server is performed for image adjustments, then image display flexibility is improved, but network load and processing time increase
Solution Approach 1:
The server pre-processes images by applying common display transformations (windowing, leveling, geometric operations) and stores the results in a cache before client requests are received. This preliminary action allows the client to retrieve pre-processed images quickly without requiring frequent real-time processing, thus reducing processing time while maintaining display flexibility.
Solution Approach 2:
The system creates and stores copies of pre-processed images in a cache memory on the server side. When the client needs an image with specific display characteristics, the system retrieves the appropriate pre-processed copy from the cache rather than performing real-time processing, thereby reducing network transfer time and processing time while maintaining the ability to provide various display options.
2Productivity
If large image data is transferred to client for processing, then image processing capability is improved, but network bandwidth consumption increases
Solution Approach 1:
The system extracts only the necessary image data and processing parameters from the server to the client. Instead of transferring complete large image datasets, the system transfers only the required image segments along with their associated display attributes (window level, width, geometric transformations), thereby reducing network bandwidth consumption while maintaining adequate processing capability for the specific display needs.
Solution Approach 2:
The server performs image processing operations (windowing, leveling, geometric transformations) in advance before data transfer to the client. By pre-processing images on the server side and storing the results, the system eliminates the need for the client to perform computationally intensive processing operations, thus maintaining image processing capability while significantly reducing network bandwidth requirements.
3Speed
If real-time image processing is performed on client, then display responsiveness is improved, but computational resources are consumed
Solution Approach 1:
The server performs computationally intensive image processing operations (windowing, leveling, geometric transformations) in advance before data transfer to the client. By pre-processing images on the server side, the system shifts the computational burden away from the client, thereby maintaining display responsiveness while significantly reducing the computational resources required on the client side.
Solution Approach 2:
The system creates and stores copies of pre-processed images in cache memory on the server. When the client requests an image, it retrieves the pre-processed copy from the cache rather than performing real-time processing, thereby achieving fast display responsiveness without consuming significant computational resources on the client device.
4Productivity
If image attributes are stored and retrieved efficiently, then display performance is improved, but data management complexity increases
Solution Approach 1:
The system stores image data along with associated display attributes (window level, width, geometric transformations) as structured parameters. By changing how image data is organized and indexed using these parameters, the system enables efficient retrieval and matching of pre-processed images based on the required display characteristics, thereby improving display performance while managing data organization through parameter-based structuring rather than complex management systems.
Data Source
AI summary
A method and apparatus are disclosed for preprocessing and storing image attributes for the accelerated display of medical images in medical applications. In at least one embodiment, the method includes: assigning image attributes to a medical image, which are characteristic of a medical application which generates a specific visual display of the medical image; adjusting the medical image in accordance with the image attributes; storing the adjusted medical image together with the image attributes; calling up a further or the same medical application, which requires a visual display of the medical image; checking whether the required image attributes for the visual display correspond to the stored image attributes; calling up the stored, modified medical image in the case of a similar or identical correspondence of the image attributes; and visually displaying the recalled medical image.