Radiographic Apparatus Bias Line Segmentation for Noise Reduction
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Solution Overview
Problem
Existing radiographic apparatuses using flat panel detectors face challenges in accurately sensing radiation irradiation due to noise interference from impacts or magnetic fields, leading to erroneous detection.
Innovation Solution
A radiographic apparatus with multiple pixel groups and bias sources, where each pixel group corresponds to a bias source, and a sensing unit that samples current values from both active and inactive pixel groups to differentiate between radiation-induced signals and noise, using a driving circuit to control switch elements and determine radiation presence based on overlapping signal values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single bias line is used to supply bias potential to pixels, then the device complexity is reduced, but the measurement precision of radiation detection deteriorates due to noise interference
Solution Approach 1:
The pixel array is divided into multiple pixel groups (first pixel group and second pixel group), each supplied by electrically independent bias lines. This segmentation allows separate sampling of bias currents from different groups, enabling noise differentiation and improving radiation detection precision without requiring a completely complex reconfiguration of the bias supply system.
Solution Approach 2:
The invention introduces a temporal dimension to the bias line sampling process by sampling bias currents at different timings (first timing for first pixel group, second timing for second pixel group). This time-based differentiation allows the system to distinguish between radiation-induced signals and noise components, improving measurement precision while maintaining a relatively simple bias line structure.
2Difficulty of detecting and measuring
If bias current is sampled from the same pixels used for image detection, then the sensing capability is maximized, but the reliability of radiation detection deteriorates due to noise from impacts or magnetic fields
Solution Approach 1:
By segmenting the pixel array into multiple groups with independent bias lines, the invention enables separate sampling of bias currents. This allows the system to compare signals from different pixel groups and identify noise components (such as those from impacts or magnetic fields) that affect both groups similarly, thereby improving reliability by reducing false positives while maintaining effective radiation sensing.
Solution Approach 2:
The invention creates a redundant sampling mechanism by sampling bias currents from multiple pixel groups at different timings. This copying approach allows the system to verify detected signals against multiple samples, distinguishing genuine radiation events from noise-induced false positives and thereby enhancing detection reliability.
3Measurement precision
If noise reduction techniques are applied to improve detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The invention implements noise reduction through segmentation of the pixel array into multiple groups with independent bias lines, requiring minimal additional hardware. The noise reduction is achieved by sampling bias currents from different groups at different timings and comparing the samples, which adds computational logic but avoids complex additional sensing hardware, thus improving measurement precision with moderate device complexity increase.
Solution Approach 2:
The invention employs periodic sampling of bias currents at different timings for different pixel groups. This periodic action allows the system to capture noise patterns and distinguish them from radiation signals through temporal analysis, achieving noise reduction and improved measurement precision through a relatively simple periodic sampling mechanism rather than complex continuous monitoring systems.
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 accuracy of radiation detection by isolating noise components, reducing false positives from impacts or magnetic fields, and providing robustness against noise-generated errors.
Implementation Method 1
a conversion element configured to convert radiation into a charge
Data Source
AI summary
A radiographic apparatus includes a plurality of pixel groups, bias sources, and a sensing unit, wherein each pixel group includes a pixel including a conversion element for converting radiation into a charge. Each bias source supplies a bias potential to the conversion element of a pixel via a bias line. The sensing unit samples a first signal value indicating a current flowing through a first bias line connected to a first pixel group including a pixel of which a switch element is turned on and a second signal value indicating a current flowing through a second bias line connected to a second pixel group where the switch element is off at timings overlapping at least in part and determines presence or absence of radiation irradiation based on the first signal value and the second signal value. The first and second bias lines have substantially same time constants.