Medical Image Preprocessing via Scan Protocol Matching
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Solution Overview
Problem
Medical image processing from medical imaging devices is resource-intensive and inefficient, leading to delays and wastage of resources due to the need for extensive processing in reading rooms, where tasks compete and often result in unused scans.
Innovation Solution
A system that preprocesses medical image data by matching scan protocols to optimized preprocessing tasks based on usage data, prioritizing tasks with higher scores and executing them in ranked order, allowing for efficient resource allocation and quicker turnaround times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If extensive preprocessing tasks are performed on scan data in the reading room, then the scan data can be transformed into a visual representation, but large outlays of resources are used and processing delays occur
Solution Approach 1:
The system performs preprocessing tasks automatically and in advance during scan acquisition, before the radiologist needs to review the images. By executing preprocessing operations proactively rather than reactively when requested, the system prepares multiple processed versions of scan data ahead of time, eliminating waiting time for radiologists while distributing computational load efficiently across the workflow
2Ease of operation
If preprocessing tasks are initiated by users at workstations, then processing can be customized, but resource intensive activities compete with other active processes and bog down workstations
Solution Approach 1:
The system extracts preprocessing functionality from the radiologist's workstation environment and relocates it to a dedicated preprocessing server or cloud-based processing infrastructure. This separation allows workstations to remain responsive for user interactions while heavy computational tasks are performed remotely, eliminating the performance bottleneck without reducing user control over processing parameters
Solution Approach 2:
The system introduces an intermediary preprocessing service layer between the imaging acquisition system and the radiologist's workstation. This intermediary automatically receives scan data, executes appropriate preprocessing tasks based on scan protocols, and delivers processed images to the workstation, shielding the radiologist from computational complexity while maintaining ease of use
3Reliability
If all scan data is processed regardless of usage, then complete visual representations are available, but resources are wasted on unused scans
Solution Approach 1:
The system implements feedback loops that monitor radiologist behavior and scan utilization patterns to dynamically adjust preprocessing decisions. By tracking which scans are actually reviewed and which preprocessing tasks are utilized, the system learns to optimize resource allocation, performing comprehensive preprocessing only when needed while reducing or eliminating processing for scans that will not be used
Solution Approach 2:
The system dynamically changes preprocessing parameters such as the level of processing detail, resolution, and task selection based on scan characteristics, expected clinical utility, and resource availability. By adjusting these parameters rather than applying fixed maximum-processing to all scans, the system maintains data completeness for important scans while reducing resource consumption for scans with limited clinical value
Data Source
AI summary
A system and method for optimizing preprocessing of medical images. Preprocessing is triggered by receiving scan results and a scan protocol without input from a reading room or user interface. The preprocessing tasks are optimized through use of matching scan protocols to sets of possible preprocessing tasks. The execution of the preprocessing tasks is optimized through use of feedback from the reading room.