Image Reconstruction via Opposing Projection Data Correction
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Solution Overview
Problem
Scatter in projection data acquired for tomographic reconstruction significantly degrades the quality and accuracy of reconstructed images in transmission CT modalities, such as Cone-Beam CT and fan-beam CT, particularly in large FOV images.
Innovation Solution
A computer-implemented method for image reconstruction that involves acquiring projection data, performing opposing projection data correction to address scatter-induced artefacts by modifying ray intensities for opposing rays acquired at 180-degree offsets, and then applying conventional image reconstruction techniques to obtain improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional tomographic reconstruction is used with large FOV, then imaging coverage is improved, but scatter-induced artefacts increase
Solution Approach 1:
The patent applies asymmetry by using different correction approaches for opposing rays based on their specific scatter characteristics. Instead of uniform correction, the method identifies and corrects asymmetric scatter patterns that arise in large FOV imaging by comparing opposing projection angles and applying differential corrections to eliminate artefacts while preserving the expanded imaging coverage.
2Measurement precision
If Monte Carlo techniques are used for scatter correction, then accuracy is improved, but computation speed deteriorates
Solution Approach 1:
The patent applies partial action by implementing scatter correction only for specific projection rays that exhibit significant scatter artefacts, rather than uniformly correcting all rays. The method selectively identifies problematic rays through quality metrics and applies correction only where needed, achieving accurate scatter removal while maintaining fast computation speeds suitable for real-time adaptive radiation therapy.
Solution Approach 2:
The patent extracts and removes scatter components from projection data using an efficient algorithm that separates scatter signals from primary beam signals. By isolating and eliminating only the scatter portion rather than recomputing entire projections, the method achieves Monte Carlo-level accuracy with significantly reduced computational overhead.
3Measurement precision
If AI scatter correction techniques are used, then scatter correction capability is improved, but computational requirements deteriorate
Solution Approach 1:
The patent applies self-service by enabling the scatter correction system to automatically adapt to changing patient configurations without external retraining. The method uses real-time feedback from projection data to dynamically adjust correction parameters, allowing the system to serve itself by learning from each scan rather than requiring complex external training processes.
4Measurement precision
If repeat scans are performed for scatter correction, then image quality is improved, but treatment time deteriorates
Solution Approach 1:
The patent applies continuity of useful action by performing scatter correction continuously during the single scan acquisition process rather than requiring separate repeat scans. The method integrates scatter correction calculations into the real-time data acquisition workflow, maintaining continuous imaging and correction operations that eliminate treatment time delays while preserving high image quality for adaptive radiation therapy decisions.
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
The method effectively reduces the contribution of scatter-induced artefacts in reconstructed images, improving image quality by enhancing contrast, homogeneity, and resolution, which is particularly beneficial for adaptive radiation therapy and medical imaging applications.
Implementation Method 1
The projection data comprises projections, which are representative of measured ray intensities corresponding to attenuated rays of radiation. Beams of rays are emitted from some radiation source, passed through the region of the patient, and subsequently detected at a detector.
Implementation Method 2
The presence of scatter in projection data acquired for tomographic reconstruction is currently a limiting factor in transmission CT modalities, such as Cone-Beam CT (CBCT) and fan-beam CT, as scatter induces significant degradation of the reconstructed image quality and accuracy.
Data Source
AI summary
A computer-implemented method of image reconstruction can comprise acquiring projection data of a region of a patient. The projection data comprising one or more projections representing measured ray intensities of attenuated rays of radiation emitted from a radiation source, passed through the patient, and detected at a detector. The detector and the radiation source are rotated about an isocentre. The method can further comprise performing opposing projection data correction to obtain modified projection data. The opposing projection data correction comprising modification of the measured ray intensities for projection data acquired at substantially 180 degrees offsets about the isocentre. The method can further comprise running an image reconstruction process on the modified projection data to obtain an image of the region of the patient.