Model-Based Patient Couch Positioning in Tomographic Devices
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Solution Overview
Problem
In clinical tomographic procedures, precise and rapid positioning of patients, especially in the vertical direction, is often inadequate due to time pressure, leading to suboptimal image quality and increased radiation exposure.
Innovation Solution
A tomographic device with a model-based positioning system that uses a trained model to automate the positioning process, incorporating a computing unit and control unit to calibrate and move the patient couch relative to the recording unit, ensuring accurate alignment of the radiological or geometrical focal point within the isocenter, utilizing 3D imaging and a touch-sensitive interface for user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual positioning by user is used, then the positioning process is simple to operate, but the positioning precision and reliability are insufficient
Solution Approach 1:
The system performs self-positioning by automatically determining the patient's anatomical landmarks and calculating the optimal positioning parameters without requiring manual measurement or adjustment by the operator. The computing unit processes imaging data to autonomously establish the recording area position relative to the isocenter.
Solution Approach 2:
The manual mechanical positioning process is replaced by an automated computing-based system that uses image processing and coordinate transformation algorithms to determine positioning parameters, substituting human manual operation with computational methods.
2Productivity
If rapid positioning is prioritized under time pressure, then the workflow efficiency is improved, but the positioning accuracy deteriorates
Solution Approach 1:
The system performs preliminary positioning calculations and parameter determination automatically before the actual tomographic recording begins. By pre-calculating the optimal positioning based on initial imaging data, the system eliminates the need for time-consuming manual adjustments during the clinical procedure.
Solution Approach 2:
The system uses feedback from imaging data to continuously monitor and adjust positioning parameters. The computing unit processes recorded data to verify positioning accuracy and makes real-time corrections to ensure the recording area is properly aligned with the isocenter.
3Reliability
If automated model-based positioning is implemented, then the positioning precision and reliability are improved, but the device complexity increases
Solution Approach 1:
The computing unit serves multiple functions: it processes imaging data, determines anatomical landmarks, calculates positioning parameters, and controls the positioning mechanism. By consolidating these functions into a single integrated system, the complexity is managed while achieving high positioning reliability.
Solution Approach 2:
A trained model acts as an intermediary between the raw imaging data and the positioning control system. The model processes the imaging data to extract relevant features and translate them into positioning parameters, simplifying the overall system architecture while improving reliability.
4Object-affected harmful factors
If conventional manual positioning is used, then the device operation is simple, but the radiation exposure increases due to repeat recordings
Solution Approach 1:
The system autonomously determines positioning parameters and executes positioning without requiring repeated manual adjustments, thereby eliminating the need for repeat tomographic recordings and the associated radiation exposure to the patient.
Data Source
AI summary
A tomographic device includes a recording unit with a central system axis, a patient couch movable along the system axis and also a radiation source and a radiation detector interacting with the radiation source. The inventors have recognized that a rapid, precise and reliable positioning of a first recording area can be achieved by the positioning being based on a trained model, wherein the model has been trained with training positions. The tomographic device therefore includes a computing unit, which is designed for calibration of a first position of the first recording area relative to the recording unit based on the trained model. Furthermore the tomographic device includes a control unit for positioning the first recording area in the first position by moving the patient couch relative to the recording unit. The tomographic device is designed for a first tomographic recording of the first recording area in the first position.