Tomosynthesis Calibration via Epipolar Geometry Consistency
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Solution Overview
Problem
Portable tomosynthesis systems face challenges in accurately determining the acquisition scan geometry due to uncertainties in the relative position and orientation of the x-ray source and detector, leading to compromised image quality and artifacts in reconstructed volumetric data.
Innovation Solution
A method for geometric calibration using epipolar geometry, which involves acquiring series of projection images, estimating epipolar lines, calculating consistency metrics, and iteratively adjusting estimates to achieve accuracy within a predetermined threshold, allowing for accurate reconstruction and display of tomosynthesis volume images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If detector positioning is done by operator placement for patient comfort, then ease of operation is improved, but measurement precision of detector position and orientation deteriorates
Solution Approach 1:
The system performs self-calibration by automatically determining the detector position and orientation through image data analysis. The calibration process uses epipolar geometry calculations and consistency metrics to autonomously establish accurate geometric parameters without requiring manual measurement or precise operator positioning, thus maintaining ease of operation while achieving high measurement precision
Solution Approach 2:
The patent replaces mechanical positioning systems with computational methods. Instead of relying on mechanical fixtures or precise manual placement to define detector geometry, the system uses image processing algorithms that calculate geometric parameters from the acquired projection images, substituting physical precision requirements with computational accuracy
2Ease of operation
If the detector is placed behind a patient in a propped position for comfort, then ease of operation is improved, but the angle between detector plane and horizontal plane becomes uncertain, worsening measurement precision
Solution Approach 1:
The system replaces mechanical angle measurement and positioning systems with computational geometry methods. By using epipolar line analysis and consistency metrics derived from multiple projection images, the system can accurately determine the detector's angular orientation relative to the scan path without requiring mechanical angle sensors or precise manual angle setting
Solution Approach 2:
The patent introduces image data as an intermediary to bridge the gap between flexible detector placement and accurate geometry determination. The projection images serve as a mediator that contains implicit geometric information, allowing the system to infer precise detector orientation angles from the image patterns without direct mechanical measurement
3Adaptability or versatility
If the detector is skewed with respect to the transport path of the x-ray source, then adaptability to patient positioning is improved, but reconstruction accuracy deteriorates due to unknown geometry
Solution Approach 1:
The system dynamically determines geometric parameters (detector skew angle, position, and orientation) based on the actual acquisition configuration rather than relying on fixed predetermined values. By calculating these parameters from image data using epipolar geometry, the system adapts to any detector orientation relative to the scan path while maintaining reconstruction accuracy
Solution Approach 2:
The calibration process uses feedback from the acquired projection images to refine the geometric parameters. The system iteratively adjusts the estimated detector geometry to maximize the consistency metric, creating a feedback loop that ensures accurate reconstruction parameters even when the detector is skewed relative to the transport path
Data Source
AI summary
A method for geometric calibration of a radiography apparatus acquires tomosynthesis projection images of patient anatomy from a detector and an x-ray source translated along a scan path. An epipolar geometry is calculated according to the relative position of the detector to the scan path by estimating a direction for epipolar lines that extend along an image plane that includes the detector. A region of interest of the patient anatomy that is a portion of each projection image and is fully included within each projection image in the series is defined. A consistency metric is calculated for estimated epipolar lines extending within the ROI. The method iteratively adjusts the epipolar line estimation until the consistency metric indicates accuracy to within a predetermined threshold. A portion of a tomosynthesis volume is reconstructed and displayed.