Autor: |
Jincong Pang, Haodi Wu, Hao Li, Tong Jin, Jiang Tang, Guangda Niu |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024) |
Druh dokumentu: |
article |
ISSN: |
2041-1723 |
DOI: |
10.1038/s41467-024-46184-0 |
Popis: |
Abstract X-ray detection is widely used in various applications. However, to meet the demand for high image quality and high accuracy diagnosis, the raw data increases and imposes challenges for conventional X-ray detection hardware regarding data transmission and power consumption. To tackle these issues, we present a scheme of in-X-ray-detector computing based on CsPbBr3 single-crystal detector with convenient polarity reconfigurability, good linear dynamic range, and robust stability. The detector features a stable trap-free device structure and achieves a high linear dynamic range of 106 dB. As a result, the detector could achieve edge extraction imaging with a data compression ratio of ~50%, and could also be programmed and trained to perform pattern recognition tasks with a high accuracy of 100%. Our research shows that in-X-ray-detector computing can be used in flexible and complex scenarios, making it a promising platform for intelligent X-ray imaging. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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