Scanning Parameter Determination via Scout Image Analysis
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Solution Overview
Problem
Manual determination of scanning parameters in medical imaging decreases efficiency and accuracy, necessitating automated methods for determining scanning scope and direction.
Innovation Solution
A method and system using a machine with a processor and storage device to obtain scout images, segment them to identify regions of interest, and determine scanning parameters such as scope and direction through trained neural network models, adjusting frames and comparing reference parameters for reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual determination of scanning parameters is used, then operator control and flexibility are maintained, but efficiency and accuracy of medical scans decrease
Solution Approach 1:
The system performs automated scanning parameter determination using AI algorithms that independently analyze scout images, identify ROIs, and calculate optimal scanning parameters without requiring manual operator intervention. The system serves itself by automatically completing tasks that previously required human operators, thereby improving scan efficiency while reducing manual operation levels.
2Measurement precision
If manual determination of scanning parameters is used, then operator judgment is applied, but accuracy of scanning parameter determination decreases
Solution Approach 1:
The patent replaces the mechanical human operator's manual determination process with an automated AI-based system that uses neural networks and image processing algorithms. This substitution eliminates human error and subjectivity in parameter determination, significantly improving measurement precision while the automated system handles the complexity that would otherwise require skilled operators.
Solution Approach 2:
The system introduces an AI algorithm as an intermediary between the scout image and the final scanning parameters. This intermediary automatically processes the image data, identifies anatomical structures, and determines optimal scanning parameters, providing consistent and accurate results without requiring direct human intervention in the parameter determination process.
3Productivity
If automated determination using AI models is used, then efficiency and accuracy are improved, but system complexity increases
Solution Approach 1:
The system performs preliminary automated analysis of scout images to determine scanning parameters before the actual medical scan begins. By pre-processing the scout images and calculating optimal parameters in advance, the system improves overall scan efficiency while containing the AI processing complexity to a preliminary stage rather than during the entire scanning process.
Data Source
AI summary
Systems and methods for determining at least one scanning parameter for a scanning by an imaging device (110) are provided. The methods may include obtaining a scout image of at least one portion of a subject (502), and determining, in the scout image, a region of interest (ROI) corresponding to the at least one portion of the subject (504). The methods may further include determining, based on the ROI, the at least one scanning parameter associated with the at least one portion of the subject for performing the scanning by the imaging device (506). Systems and methods for evaluating a scanning parameter are further provided. The methods may include determining a scanning parameter associated with the ROI (1606) and obtaining a reference scanning parameter associated with the ROI (1608). The methods may further include determining whether the scanning parameter needs to be adjusted by comparing the scanning parameter and the reference scanning parameter (1610).