Medical Imaging System Parameter Optimization
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Solution Overview
Problem
Current medical imaging systems often require increased radiation doses and extended scanning times to ensure high-quality images, leading to unnecessary exposure and discomfort for patients.
Innovation Solution
A method and system that determine optimal procedure parameters, such as imaging scan and image reconstruction parameters, using a prior information database to minimize radiation dose while maintaining image quality, by obtaining feature information of a target subject, determining simulation values, and generating simulated images to select the best parameter settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the dose of imaging medium is increased to ensure sufficient image quality, then image quality is improved, but radiation exposure to the patient increases
Solution Approach 1:
The system dynamically adjusts imaging parameters (such as tube current, tube voltage, scan time) based on patient-specific features and prior information to optimize the balance between image quality and radiation dose. By changing parameters adaptively rather than using fixed high doses, the system maintains diagnostic quality while minimizing radiation exposure.
Solution Approach 2:
The system uses simulated images generated from prior information and feature data to predict optimal imaging parameters before actual scanning. These simulated images serve as copies that guide parameter selection, allowing the system to choose doses that would produce sufficient image quality without actually delivering excessive radiation to the patient.
2Measurement precision
If scanning time is extended to ensure sufficient imaging data, then image quality is improved, but patient discomfort increases
Solution Approach 1:
The system performs preliminary determination of optimal scanning parameters by analyzing patient features and accessing prior information before the actual scanning begins. This preliminary action allows the system to set scan time and other parameters to achieve sufficient image quality in the minimum necessary time, avoiding unnecessary patient discomfort.
3Ease of operation
If manual determination of procedure parameters is used, then ease of operation is maintained, but parameter selection variability increases
Solution Approach 1:
The system automatically determines optimal procedure parameters by analyzing patient features and prior information without requiring manual intervention. This self-service approach eliminates variability in parameter selection that arises from different operator preferences or experiences, while maintaining ease of use through automated decision-making.
4Ease of operation
If standardized scan protocols are used, then ease of operation is improved, but adaptability to individual patients decreases
Solution Approach 1:
The system transitions from static, fixed scan protocols to dynamic parameter adjustment based on real-time analysis of patient features and prior information. This dynamic approach maintains the simplicity of standardized protocols while adding the adaptability to optimize parameters for each individual patient, achieving both ease of operation and patient-specific customization.
Data Source
AI summary
The present disclosure is related to systems and methods for imaging. The method includes obtaining feature information of a target subject. The method includes obtaining target prior information of the target subject based on the feature information of the target subject and a prior information database. The prior information database includes prior information of a plurality of candidate subjects. The method includes determining, based on the target prior information of the target subject, a value of a procedure parameter that relates to a procedure of the target subject using a medical device