Digital Pulse Processing for Multi-Spectral Photon Counting
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Solution Overview
Problem
Conventional multi-spectral photon counting detectors face issues with pulse pile-up, where overlapping photon pulses obscure each other's amplitudes, leading to incorrect energy discrimination and distribution of detected photons in computed tomography systems.
Innovation Solution
The implementation of a local minimum identifier and a pulse pile-up error corrector that corrects for energy-discrimination errors by identifying local minima between overlapping pulses, ensuring each detected photon is accurately counted across multiple energy thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional pulse processing is used in high-count-rate photon detection, then detection speed increases, but pulse pile-up occurs causing amplitude distortion and energy discrimination errors
Solution Approach 1:
The patent applies preliminary action by performing deconvolution processing on the composite signal to separate overlapping pulses before energy discrimination. The system identifies pulse peaks and performs mathematical deconvolution to recover individual pulse amplitudes, correcting pile-up effects before the energy threshold comparison stage, thus maintaining both high detection rates and accurate energy measurement
Solution Approach 2:
The patent introduces an intermediary processing stage between signal amplification and energy discrimination. This intermediary deconvolution module acts as a mediator that separates the composite signal from overlapping pulses, enabling accurate energy measurement even at high count rates where pulses would otherwise overlap and distort each other's amplitudes
2Measurement precision
If multiple energy thresholds are used for spectral discrimination, then energy resolution improves, but the complexity of the discrimination circuit increases
Solution Approach 1:
The patent replaces complex hardware discrimination circuits with software-based deconvolution processing. Instead of using multiple physical comparators and complex logic circuits for multi-threshold discrimination, the system uses digital signal processing algorithms to separate pulses and determine their energies, reducing hardware complexity while maintaining or improving energy resolution
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 solution effectively corrects for pulse pile-up errors, providing accurate energy resolution and distribution of detected photons, enhancing the precision of energy-resolved data in computed tomography systems.
Implementation Method 1
a sensor that detects photons that traverse the examination region and produces an electrical current pulse for each detected photon
Data Source
AI summary
An apparatus includes a local minimum identifier (408) that identifies a local minimum between overlapping pulses in a signal, wherein the pulses have amplitudes that are indicative of the energy of successively detected photons from a multi-energetic radiation beam by a radiation sensitive detector, and a pulse pile-up error corrector (232) that corrects, based on the local minimum, for a pulse pile-up energy-discrimination error when energy-discriminating the pulses using at least two thresholds corresponding to different energy levels. This technique may reduce spectral error when counting photons at a high count rate.