Scan Parameter Prediction for Medical Imaging
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Solution Overview
Problem
Current medical scanning technologies face challenges in simulating the effect of contrast agent injection on physiological motion and optimizing scan parameters for individual patients, leading to potential unnecessary radiation exposure and inefficiencies.
Innovation Solution
A system that uses a processor to predict scan parameters based on pre-scanned physiological motion data and health information, utilizing estimation and recommendation models to automate the determination of optimal scan settings, reducing reliance on user experience and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scan parameters are set manually by a user, then the user can adjust parameters based on experience, but the process requires extensive user experience and is not efficient or accurate for personalized optimization
Solution Approach 1:
The system automatically determines scan parameters by processing patient physiological data and health information through estimation and recommendation models, eliminating the need for manual user adjustment and extensive user experience while achieving personalized optimization
Solution Approach 2:
The manual parameter setting process is replaced by an automated computational system that uses machine learning models to predict and recommend optimal scan parameters based on patient-specific data, substituting human expertise with an intelligent algorithm
2Reliability
If scan range and scan times are increased to improve scan success rate, then the chances for successful scan increase, but the patient is exposed to unnecessary radiation
Solution Approach 1:
The system dynamically adjusts scan parameters including scan range, scan times, and radiation dose based on predicted physiological motion data and patient-specific characteristics, achieving optimal scan success rate while minimizing unnecessary radiation exposure through personalized parameter optimization
3Measurement precision
If contrast agent injection is used during scan, then image quality and time resolution improve, but the physiological motion of the subject is affected
Solution Approach 1:
The system performs preliminary estimation of physiological motion parameters before the actual scan by processing pre-scan physiological data, and uses this information to predict and compensate for motion effects during contrast agent injection, allowing optimization of scan parameters to account for anticipated physiological changes
Data Source
AI summary
Systems and methods for scan preparation are provided. The systems may obtain a first parameter set of a subject to be scanned by a medical device acquired before a scan is performed on the subject. The first parameter set may relate to a physiological motion of the subject acquired before the scan is performed on the subject. The systems may predict, based on the first parameter set and an estimation model, a second parameter set of the subject. The second parameter set may relate to the physiological motion of the subject. The systems may determine at least one scan parameter for the scan based at least in part on the second parameter set. The systems may cause the medical device to perform the scan on the subject based on the at least one scan parameter.