Scout Imaging Range Specification with Adaptive Feature-Point Detection
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Solution Overview
Problem
Existing imaging systems face challenges in accurately detecting feature points on subjects during scout imaging due to subject movement and partial coverage, which can lead to inaccuracies in specifying the imaging range for three-dimensional image acquisition.
Innovation Solution
An information processing apparatus that selects between a first detection model prioritizing frame rate and a second model prioritizing accuracy based on the imaging part and movement of the subject to detect feature points and specify the imaging range, with the first model having a higher processing speed and the second model providing higher accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single detection model is used for feature point detection, then the system is simple to operate, but the detection accuracy decreases when the subject moves or is partially covered
Solution Approach 1:
The system dynamically switches between different detection models based on real-time conditions such as subject movement and coverage status. The controller selects the first detection model when the subject is stationary and fully visible, and switches to the second detection model when movement or partial coverage is detected, optimizing detection accuracy for varying operational conditions.
2Productivity
If the first detection model prioritizing frame rate is used, then the processing speed is high, but the detection accuracy is lower
Solution Approach 1:
The system dynamically adjusts the detection model selection based on subject stability. When the subject is stationary and fully visible, the first detection model with higher frame rate is used for efficient processing. When movement or partial coverage is detected, the system switches to the second detection model that prioritizes accuracy, thus optimizing the trade-off between processing speed and detection accuracy according to real-time conditions.
3Measurement precision
If the second detection model prioritizing accuracy is used, then the detection accuracy is high, but the processing speed is lower
Solution Approach 1:
The system employs conditional switching between detection models. The second detection model with higher accuracy is selectively activated only when the controller detects subject movement or partial coverage, rather than running continuously. This dynamic approach ensures high detection accuracy is achieved when needed, while maintaining higher processing speeds during normal stable conditions.
4Measurement precision
If manual setting of imaging range is performed, then the imaging range can be precisely adjusted, but the operation time increases
Solution Approach 1:
The system performs automatic imaging range specification by detecting feature points and calculating the imaging range based on the detected positions. This self-service approach eliminates the need for manual operator intervention in setting the imaging range, thereby reducing operation time while maintaining precision through accurate feature point detection using the selected detection models.
Data Source
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AI summary
A processor (11) acquires a camera image generated by capturing a moving image of a subject on an examination table via a camera (7), selects one detection model from among a plurality of detection models including a first detection model that places importance on a frame rate in a case of detecting the feature points and a second detection model that places importance on accuracy in a case of detecting the feature points, which are constructed so as to detect a plurality of feature points on the subject included in the camera image, detects the plurality of feature points on the subject included in the camera image by using the selected detection model, and specifies an imaging range of the subject based on the plurality of feature points.