Radiation Detector Photon Counting Pixel Segmentation
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Solution Overview
Problem
Current radiation detectors for medical imaging, such as CT and X-ray systems, face challenges in accurately sorting and counting photons across multiple energy bands, which limits the precision of multi-energy imaging and increases pixel size, hindering the generation of high-quality cross-sectional images.
Innovation Solution
A radiation detector with a plurality of pixels, each equipped with a radiation absorbing layer and a photon processor, compares electrical signals with reference values to sort and count photons based on energy bands, allowing for differential reference values between pixels or sub-pixels, enabling precise photon counting and image reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional radiation detectors are used to sort and count photons across multiple energy bands, then the precision of multi-energy imaging is limited and pixel size increases, but if advanced photon processing is implemented, then manufacturing complexity increases
Solution Approach 1:
The radiation detector is divided into multiple pixels, each independently equipped with a radiation absorbing layer and a photon processor. Each photon processor further segments the detection task by comparing electrical signals against multiple reference values to sort photons into different energy bands. This segmentation enables precise multi-energy imaging while distributing the complexity across modular units rather than requiring a monolithic complex structure.
Solution Approach 2:
Each pixel is configured with local reference values stored in storage units within that specific pixel, rather than using a centralized reference system. This local quality approach allows each pixel to independently perform energy band sorting with its own optimized reference values, improving measurement precision for multi-energy imaging while keeping each pixel's structure relatively simple and manageable.
2Measurement precision
If multiple reference values are stored in each pixel for sorting photons into energy bands, then photon counting accuracy improves, but the storage requirements and device complexity increase
Solution Approach 1:
Each pixel contains storage units that hold reference values local to that pixel's detection characteristics. This local storage approach enables accurate photon counting by comparing incoming photon signals against locally-stored reference values specific to different energy bands, improving measurement precision while distributing storage requirements across multiple pixels rather than requiring centralized storage.
Solution Approach 2:
The storage function is segmented and distributed to individual pixels rather than centralized. Each pixel has its own storage units containing reference values for energy band sorting, which enables independent and accurate photon counting in each pixel while the overall system manages total storage requirements through this distributed architecture.
3Measurement precision
If radiation detectors accurately detect radiation passing through the object, then medical image reconstruction accuracy improves, but the complexity of the detection system increases
Solution Approach 1:
The detection system is segmented into multiple independent pixels, each with its own radiation absorbing layer and photon processor. This segmentation allows accurate radiation detection across multiple energy bands while managing system complexity through modular design, where each pixel operates semi-independently to contribute to overall image reconstruction accuracy.
Solution Approach 2:
The system utilizes changes in electrical signal parameters (voltage levels) corresponding to different photon energy levels. By comparing these electrical signal parameters against stored reference values, the system accurately detects and sorts photons into energy bands, improving medical image reconstruction accuracy through parameter-based discrimination rather than complex structural arrangements.
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 enhances the accuracy of multi-energy imaging by allowing for more precise sorting and counting of photons, reducing pixel size, and improving the quality of cross-sectional images in medical imaging applications.
Implementation Method 1
a radiation absorbing layer configured to convert photons incident on the radiation absorbing layer into a first electrical signal
Data Source
AI summary
A radiation detector includes a plurality of pixels configured to detect radiation, and at least one of the plurality of pixels includes a radiation absorbing layer configured to convert photons incident on the radiation absorbing layer into a first electrical signal, and a photon processor including a plurality of storages configured to count and store the number of the photons based on the first electrical signal. At least one of the plurality of storages is configured to compare the first electrical signal with a first reference value to obtain a second electrical signal, and count and store the number of the photons based on a third electrical signal that is obtained based on a comparison of the second electrical signal with a second reference value.