ROI Tomography Scanning Trajectories for X-ray Flux Optimization
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Solution Overview
Problem
Computed Tomography (CT) systems face challenges in achieving high-quality images of regions of interest (ROI) due to limitations in x-ray flux caused by large focus-object distances and conventional scanning trajectories, which result in reduced resolution and signal-to-noise ratio.
Innovation Solution
The implementation of optimized scanning trajectories that minimize focus-object distances by selecting viewing angles based on the circumradius of the sample, allowing for eccentric rotation and reduced focus-object distances, thereby increasing x-ray flux and scan efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional scanning trajectories are used, then the scan covers the entire sample, but the focus-object distance is large resulting in reduced x-ray flux and lower image quality
Solution Approach 1:
The patent applies local quality by designing scanning trajectories that concentrate x-ray exposure on the region of interest (ROI) rather than uniformly scanning the entire sample. By identifying the ROI coordinates and calculating optimized trajectories that pass closer to the ROI, the system delivers higher x-ray flux specifically to the region requiring high-quality imaging, while reducing exposure to other areas. This resolves the contradiction by improving image quality locally without requiring increased overall x-ray flux.
Solution Approach 2:
The patent implements dynamics by making the scanning trajectory adaptive and variable rather than fixed. The trajectory is dynamically optimized based on the ROI location, allowing the x-ray source to follow a path that minimizes focus-object distance to the ROI. This dynamic adjustment of the scanning path enables the system to achieve higher x-ray flux at the ROI while maintaining efficient scanning, resolving the contradiction between image quality and x-ray flux utilization.
2Quantity of substance
If the focus-object distance is reduced to increase x-ray flux, then image quality improves, but the scanning trajectory becomes more complex and time-consuming
Solution Approach 1:
The patent applies preliminary action by pre-calculating the optimized scanning trajectory before the actual scan begins. The system identifies the ROI coordinates, computes the optimal path that minimizes focus-object distance to the ROI, and determines the precise viewing angles in advance. This preliminary optimization ensures that during the actual scanning process, the system follows an efficient trajectory that maximizes x-ray flux to the ROI without requiring additional scan time or complex real-time adjustments.
Solution Approach 2:
The patent implements parameter changes by optimizing the scanning trajectory parameters (viewing angles, path coordinates, focus-object distance) based on the ROI location. By mathematically determining the optimal set of parameters that minimize the focus-object distance to the ROI while maintaining complete coverage, the system achieves higher x-ray flux without proportionally increasing scan time. The parameter optimization resolves the contradiction by finding the most efficient configuration.
3Manufacturing precision
If conventional trajectories are used, then scanning is simple and fast, but the resolution and signal-to-noise ratio of ROI images are insufficient
Solution Approach 1:
The patent applies self-service by enabling the scanning system to automatically optimize its own trajectory based on the ROI location without requiring manual intervention or complex external control. The system identifies the ROI coordinates, calculates the optimal trajectory parameters, and executes the optimized scan autonomously. This self-optimizing capability achieves high-resolution ROI imaging while keeping the operational complexity low, as the system performs the optimization automatically rather than requiring complex manual trajectory design.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the quality of ROI scans by increasing x-ray flux and reducing artifacts, resulting in higher resolution and signal-to-noise ratio images while maintaining efficient scanning trajectories.
Implementation Method 1
Computed Tomography (CT) uses x-rays to investigate samples, and includes obtaining data of internal structure
Data Source
AI summary
Apparatuses and methods for implementing scanning trajectories for ROI tomography are disclosed herein. An example method includes determining a first focus object distance based on a circumradius of a sample, the sample including a region of interest, determining a second focus object distance based on a radius of a smallest cylinder that contains the region of interest, determining a plurality of viewing angles from a plurality of possible viewing angles in response to the first focus object distance, where each viewing angle of the plurality of viewing angles has an associated focus object distance measured from the region of interest, and where the associated focus object distance of each of the plurality of viewing angles is less than the first focus object distance and greater than the second focus object distance, and scanning the region of interest using at least the plurality of viewing angles.