X-ray Detector Beam Detection with Null Row Reference
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Solution Overview
Problem
Current digital radiographic detectors face challenges in reliably detecting x-ray beam-on and beam-off events in real-time, particularly in tightly collimated images and amidst external electromagnetic interference, leading to image artifacts and potential re-takes due to missed or false triggers.
Innovation Solution
A method involving sequential capture of image frames, including dark images, where statistical measures of pixel subsets in current frames are compared to stored dark images to detect x-ray beam impact, with additional frames captured and subtracted to form exposed radiographic images, utilizing an on-board image processing unit for robust beam detection and image correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous readout mode is used for real-time beam detection, then beam-on and beam-off events can be detected in real-time, but false triggers may occur due to external electromagnetic interference and noise sources
Solution Approach 1:
The detector output is divided into multiple rows, with specific attention to null rows that contain no image information. By segmenting the readout into information-bearing rows and null rows, the system can compare signals to distinguish true beam events from electromagnetic interference, thereby maintaining reliability while filtering noise.
Solution Approach 2:
Null rows serve as an intermediary reference that contains no x-ray image information but captures the same electromagnetic interference and noise as image rows. By using null rows as a mediator for comparison, the system can identify and reject false triggers caused by external interference while maintaining real-time detection capability.
2Measurement precision
If beam detection threshold is lowered to detect tightly collimated images, then detection sensitivity increases, but false beam-on detection may occur due to low signal levels
Solution Approach 1:
Null rows act as an intermediary reference that captures noise and interference without x-ray signal. By comparing image row signals against null row signals, the system can set appropriate detection thresholds that maintain sensitivity for tightly collimated images while using the null rows as a mediator to identify and reject false positives caused by low signal levels or noise.
Solution Approach 2:
The detection threshold is dynamically adjusted based on the statistical properties of null rows. By changing the threshold parameter adaptively rather than using a fixed value, the system maintains high sensitivity for detecting low-signal tightly collimated images while preventing false triggers through statistically-based threshold setting.
3Measurement precision
If multiple dark images are captured and averaged for noise reduction, then measurement precision improves, but time delay increases before beam detection
Solution Approach 1:
Null rows are captured continuously in advance alongside image rows, so when beam detection is needed, the reference data is already available immediately. This preliminary capture of null rows eliminates the need to wait for multiple dark images to accumulate, providing both noise reduction and immediate beam detection capability without time delay.
4Productivity
If continuous readout is implemented, then real-time processing capability is achieved, but parasitic capacitance between photodiodes and data line increases causing additional dark signal in images
Solution Approach 1:
The parasitic capacitance signal is extracted and isolated by reading null rows that contain no x-ray image information. By separating the parasitic signal from the image signal through the null row mechanism, the system can measure and subsequently subtract the parasitic capacitance contribution, maintaining real-time processing while removing the harmful dark signal artifact.
Solution Approach 2:
The parasitic capacitance, which normally creates harmful dark signal artifacts, is converted into a useful measurement reference through null rows. By intentionally capturing the parasitic signal in null rows, the system transforms this harmful effect into a beneficial reference that can be subtracted from image rows, thereby eliminating the artifact while maintaining real-time processing capability.
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 robustness of beam detection, reduces image artifacts, and minimizes re-takes by accurately identifying beam events and correcting for parasitic capacitance-induced noise, ensuring high-quality radiographic images.
Implementation Method 1
a current digital radiographic detector may include an array of photodiodes
Implementation Method 2
there is some additional dark signal in the images during the period, when the beam is on. This is caused by parasitic capacitance between the photodiodes and the data line
Data Source
AI summary
A method of operating a DR detector including sequentially capturing image frames in the detector that include at least one dark image. The dark image is stored and a statistical measure for a subset of pixels in a captured image frame is compared with the same statistical measure of a subset of pixels in the stored dark image to detect an x-ray beam impacting the detector. An x-ray beam-on condition is indicated if a sufficient difference in intensity between the pixel subsets is detected. At least one more image frame is captured in the detector after detecting the x-ray beam. The current captured image and the at least one more image frame are added and the dark image is subtracted to form the exposed radiographic image.