Medical Image Post-Processing Automation
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Solution Overview
Problem
Medical imaging techniques face challenges in ensuring the reliability and accuracy of image processing due to inconsistent data quality and the need for manual input to determine post-processing operations, making the process time-consuming and inefficient.
Innovation Solution
A method and system for determining a scanning protocol that includes parameter values for post-processing operations, such as whether and how to perform operations like organizational analysis, ROI segmentation, and noise reduction, based on feature information and user input, to automate the image processing workflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual input is required to determine post-processing operations, then the doctor can control the processing workflow, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary analysis of imaging data to automatically determine which post-processing operations should be performed before the doctor needs to make decisions. The determination module pre-identifies suitable post-processing operations based on imaging data characteristics, reducing the time and effort required during the actual processing workflow.
2Productivity
If post-processing operations are performed on acquired imaging data without verification, then the process is simple and fast, but the reliability and image quality cannot be ensured
Solution Approach 1:
The system implements a feedback mechanism where the determination module continuously monitors imaging data quality and automatically adjusts post-processing operation selection based on detected data characteristics. This closed-loop approach ensures that only appropriate post-processing operations are performed, maintaining both high processing speed and reliable image quality through automatic verification and adaptation.
3Measurement precision
If the doctor needs to input instructions for each post-processing operation, then precise control is achieved, but the workflow becomes complex and inefficient
Solution Approach 1:
The determination module enables the system to serve itself by automatically analyzing imaging data characteristics and selecting appropriate post-processing operations without requiring detailed manual instructions from the doctor. The system self-determines the processing workflow based on predefined criteria and data quality metrics, simplifying the interface while maintaining precise control over which operations are performed.
Data Source
AI summary
The present disclosure provides methods and systems for image processing. The methods may include determining a scanning protocol of a medical scan of a target subject. The scanning protocol may include a first parameter value of a first operation parameter of each of one or more post-processing operations. The first operation parameter of a post-processing operation may relate to whether the post-processing operation needs to be performed on target imaging data collected in the medical scan. The methods may include obtaining the target imaging data of the target subject collected in the medical scan that is performed according to the scanning protocol. The methods may further include performing at least part of the one or more post-processing operations on the target imaging data based on the first parameter value of the first operation parameter of each of the one or more post-processing operations.