CT Reconstruction ROI Segmentation for Artifact-Free High Resolution
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Solution Overview
Problem
Current CT reconstruction methods face limitations in achieving high resolution, especially for large objects, due to the finite extent of radiation sources and detector elements, leading to artifacts and reduced image quality when the object is not fully imaged in each projection.
Innovation Solution
Generating a first projection data set with low resolution and a second data set with higher resolution focused on the object region of interest, then combining these using specific rules to achieve artifact-free high-resolution CT reconstructions within the region of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the object is completely imaged in each projection to avoid artifacts, then the reconstruction reliability is improved, but the spatial resolution deteriorates due to limited optical magnification
Solution Approach 1:
The patent divides the object into two regions: a region of interest (ROI) and the remaining object area. Different imaging strategies are applied to each region - the ROI is imaged with high spatial resolution using optimized magnification, while the remaining area is imaged to ensure complete object coverage. This segmentation allows simultaneous achievement of high resolution in the ROI and artifact-free reconstruction overall.
Solution Approach 2:
The patent applies different quality standards to different parts of the object. The region of interest receives high-resolution imaging with optimized magnification factors, while other areas use standard imaging parameters. This local differentiation enables high spatial resolution where needed without compromising the overall reconstruction reliability.
2Area of stationary object
If the object is positioned far from the detector to reduce magnification, then the complete object can be imaged, but the spatial resolution deteriorates
Solution Approach 1:
The patent segments the imaging task into two parts: imaging the complete object at standard magnification for coverage, and imaging the region of interest at high magnification for resolution. This allows the object to be positioned for complete coverage while still achieving high resolution in the ROI through the segmented approach.
Solution Approach 2:
The patent introduces a temporal dimension by acquiring multiple projection data sets at different magnification factors. Instead of trying to achieve both complete coverage and high resolution in a single static image, the solution acquires data at different magnifications and combines them, effectively adding the time dimension to resolve the spatial contradiction.
3Manufacturing precision
If multiple projection data sets with different magnifications are acquired, then the spatial resolution in the region of interest is improved, but the measurement time increases
Solution Approach 1:
The patent segments the projection acquisition into two sets: one set acquired at standard magnification for complete object coverage, and another set acquired at high magnification specifically for the region of interest. By segmenting the acquisition strategy, the measurement time is optimized - only the necessary high-resolution data for the ROI is acquired at high magnification, rather than acquiring all data at high magnification.
Solution Approach 2:
The patent applies partial action by acquiring projection data at high magnification only for the region of interest rather than for the entire object. This partial high-resolution acquisition reduces the total measurement time compared to acquiring complete high-resolution data sets, while still achieving the desired spatial resolution in the critical ROI.
4Manufacturing precision
If the region of interest is recorded with higher resolution, then the manufacturing precision is improved, but the device complexity increases due to multiple detectors or repeated measurements
Solution Approach 1:
The patent makes the detection system multi-functional by using a single detector that can operate at different magnification factors. The same detector acquires both the complete object projection data and the high-resolution ROI projection data by adjusting the magnification, eliminating the need for multiple specialized detectors and reducing system complexity.
Solution Approach 2:
The patent introduces dynamic adjustability to the magnification factor during the imaging process. The magnification can be changed between acquiring different projection data sets, allowing the system to adapt between standard and high-resolution modes. This dynamic capability enables high spatial resolution in the ROI without requiring a permanently complex multi-detector system.
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
Enables detailed, artifact-free CT imaging of specific object regions with improved resolution, overcoming the limitations of standard CT reconstruction algorithms by varying magnification and using detectors with different spatial resolutions or X-ray energies.
Implementation Method 1
the radiation source, i. H. the area from which the radiation used for tomography is emitted (e.g. the focal point of an X-ray tube)
Implementation Method 2
the object must be completely imaged horizontally on each two-dimensional shadow image (projection)
Data Source
Figure 1
Figure 2A~2B
Figure 3
AI summary
The invention relates to a CT reconstruction of an object (4) having a high-resolution object region (10) of interest, which may be created in an artifact-free manner in that a first projections data set of a first region (4) of the object comprising the object region (10) of interest is created using at least one first projection image of a first resolution, and a second projection data set of the object region (4) of interest is created using at least one second projection image at a second, higher resolution. The first and the second projection data sets may be combined in accordance with a combination rule in order to obtain a CT reconstruction (66) of the first region of the object (4) in the first resolution, and the object region (10) of interest in the second, higher resolution.