Medical Imaging Parameter Determination via Subject Height Data
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Solution Overview
Problem
Current medical examination systems face inefficiencies in determining accurate and efficient examination parameters for imaging devices, leading to inconvenience for subjects and increased workload for operators, as existing methods often require manual correction of parameters and may involve unnecessary radiation exposure.
Innovation Solution
A method and system that utilize computing devices to obtain height data of subjects, determine target regions for imaging devices, and calculate movement parameters to accurately position the subject for scanning, potentially breaking down large scans into sub-scans if necessary, and updating examination parameters based on historical data to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual determination of examination parameters is used, then flexibility and adaptability are improved, but workload and time consumption increase
Solution Approach 1:
The system automatically determines examination parameters by processing subject information (height, weight, examination type) through a database lookup mechanism. The parameter determination unit queries the database using subject attributes and automatically retrieves appropriate parameters without requiring manual operator input, making the system self-serve the parameter determination task while maintaining adaptability to different subject characteristics
Solution Approach 2:
The database is pre-populated with examination parameters for different subject types and examination scenarios. By preparing the parameter database in advance with various parameter sets corresponding to different height ranges, weight ranges, and examination types, the system enables rapid automatic retrieval during actual examinations, eliminating the need for manual parameter determination while maintaining flexibility
2Productivity
If automatic parameter determination is used, then productivity is improved, but measurement precision may worsen
Solution Approach 1:
The database stores different parameter sets tailored to specific subject characteristics (different height ranges, weight ranges, examination types). By matching the subject's specific attributes to the corresponding localized parameter set in the database, the system ensures that the most appropriate parameters are selected for each individual case, maintaining high precision while enabling automatic determination
Solution Approach 2:
The system automatically adjusts examination parameters based on subject-specific attributes by querying the database with subject information and retrieving the corresponding parameter set. This dynamic parameter selection process ensures that parameters are optimized for each subject's characteristics while maintaining high determination accuracy through the structured database organization
3Measurement precision
If comprehensive scanning is performed, then measurement precision is improved, but harmful factors increase
Solution Approach 1:
The system extracts and determines the specific target region within the subject's body based on the examination type and subject attributes before performing scanning. By identifying and isolating only the necessary examination region rather than scanning the entire body, the system maintains measurement precision for the target area while significantly reducing unnecessary radiation exposure to other body parts
Solution Approach 2:
The examination process is segmented into targeted regional scanning based on predetermined parameter determination. The system divides the scanning task into specific anatomical regions or target areas that need examination, rather than performing comprehensive full-body scanning. This segmentation maintains diagnostic accuracy for the target region while minimizing harmful radiation exposure to non-target areas
Data Source
AI summary
Systems and methods for determining one or more target examination parameters is provided. The methods may include obtaining target examination information of a subject and generating one or more initial examination parameters based on the target examination information. The methods may further include obtaining one or more historical examination parameters associated with the subject and updating at least one of the one or more initial examination parameters based on the one or more historical examination parameters to obtain one or more target examination parameters. The one or more target examination parameters may be used for performing a target examination on the subject.