CT Scan Parameter Configuration from RGB-Depth Patient Imaging
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Solution Overview
Problem
In CT scans, manual configuration of scan parameters based on patient height and weight is inefficient and prone to errors, especially when accurate patient information is unavailable or when operators lack experience.
Innovation Solution
An apparatus and method using a three-dimensional camera to acquire RGB and depth images, employing deep learning neural networks for segmentation and computation of physical parameters, automatically configuring scan parameters without patient input, including preprocessing and consideration of supporting member information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration of scan parameters is used, then operators can adjust parameters based on patient information, but the process is inefficient and prone to errors when patient information is unavailable or operators lack experience
Solution Approach 1:
The system performs self-measurement of patient body parts using the depth camera and segmentation model, automatically obtaining physical parameters without requiring manual input from operators or patients. The configuration unit then automatically sets scan parameters based on these measured parameters, enabling the system to serve itself and eliminate human error in information provision.
Solution Approach 2:
The patent replaces the manual mechanical process of measuring and configuring parameters with an automated vision-based system. The depth camera captures spatial information, the segmentation model processes images to extract body part dimensions, and the configuration unit automatically translates these measurements into scan parameters, substituting manual operations with automated computational processes.
2Measurement precision
If manual input of patient information is required, then accurate data can be obtained, but the process becomes time-consuming and fails when patients cannot provide information
Solution Approach 1:
The system performs preliminary measurement of patient physical parameters using the depth camera before the actual CT scan begins. The segmentation model processes the captured images to extract body part dimensions in advance, so that when the scan needs to start, all necessary measurement data is already available, eliminating time loss during the scanning process.
Solution Approach 2:
The patent introduces an intermediary measurement system consisting of the depth camera and segmentation model that acts as a bridge between the patient and the CT scan configuration. Instead of directly requiring patient input or manual measurement, this intermediary system automatically captures and processes visual information to obtain the necessary physical parameters.
3Productivity
If automated configuration using image processing is used, then efficiency and standardization improve, but the system complexity increases
Solution Approach 1:
The patent segments the complex automated configuration system into distinct functional modules: the depth camera for capturing spatial information, the segmentation model for processing images and extracting body part dimensions, and the configuration unit for translating measurements into scan parameters. This segmentation makes the complex system more manageable and easier to implement by breaking it down into independent, well-defined components.
Data Source
AI summary
An apparatus and method for configuring scan parameters for an imaging system are described. The method for configuring scan parameters includes acquiring an RGB image and a depth image of a scan object, computing physical parameters of the scan object according to the RGB image and the depth image of the scan object, and configuring, according to the physical parameters, scan parameters for scanning the scan object. In this way, the scan parameters for scanning the scan object can be automatically configured, which improves the efficiency and standardization of a scan process. Moreover, an appropriate configuration of scan parameters can further avoid rescanning and poor-quality scout images resulting from manual errors. An example apparatus that may be used to perform the method includes an acquisition unit for acquiring the RGB image, a first computation unit for computing the physical parameters, and a configuration unit for configuring the scan parameters.