Tomography Apparatus Predicting Start Point via Hounsfield Unit Changes
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Solution Overview
Problem
Current tomography methods using X-rays face challenges in accurately predicting the start point for imaging after contrast media injection, leading to potential overexposure of patients to radiation and suboptimal contrast enhancement.
Innovation Solution
A tomography apparatus and method that utilize an image processor and controller to reconstruct partial images from limited angle sections, track changes in Hounsfield Unit (HU) values over time, and determine the optimal start point for tomography based on predicted HU value changes, reducing radiation dose and enhancing contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tomography is performed after contrast media injection, then contrast enhancement is improved, but radiation exposure increases
Solution Approach 1:
The system performs preliminary monitoring of HU values at multiple points before the actual tomography scan to predict the optimal start point. By advance determination of when contrast enhancement will be optimal, the system avoids unnecessary radiation exposure while ensuring contrast quality when imaging does occur.
Solution Approach 2:
The system continuously monitors HU value changes in real-time during the contrast media injection process and uses this feedback to dynamically adjust the tomography start point. The controller compares actual HU values with predicted values and determines the optimal imaging moment based on this feedback loop.
2Productivity
If tomography start point is determined without accurate prediction, then imaging can be performed, but radiation dose increases due to unnecessary scans
Solution Approach 1:
The system performs preliminary monitoring and prediction of HU values before initiating the actual tomography scan. Multiple prediction points are established in advance, and the optimal start point is determined through preliminary analysis of contrast media distribution patterns.
Solution Approach 2:
The system uses the object's own HU value changes as a natural indicator to determine the optimal imaging moment. The contrast media injection process itself provides the information needed to trigger imaging, eliminating the need for external timing mechanisms or trial-and-error scanning.
3Measurement precision
If multiple prediction points are used to monitor HU values, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The monitoring process is divided into multiple discrete prediction points (first prediction point, second prediction point, etc.) along the tomography path. Each prediction point monitors HU values independently, allowing the system to identify the optimal start point through comparison of segmented measurement locations.
Solution Approach 2:
The same HU value monitoring mechanism is used for multiple prediction points without requiring separate physical systems. The controller performs multiple predictions using the same hardware resources, making the multi-point monitoring system cost-effective and space-efficient.
Data Source
AI summary
A tomography apparatus includes an image processor configured to obtain a first image, which is a partial image of an object, by using data obtained from a first angle section corresponding to a first point, and to obtain a second image, which is a partial image of the object, by using data obtained from a second angle section corresponding to a second point subsequent to the first point; and a controller configured to obtain first information representing a brightness change, to obtain second information representing a rate of change in a Hounsfield unit (HU) value between the first point and the second point based on the first information, and to determine a tomography start point of the object based on the second information.