Zobrazeno 1 - 10 of 24 pro vyhledávání: '"Jiongtao, Zhu"'
1
Akademický článek
Dynamic X-ray imaging with screen-printed perovskite CMOS array
Autor: Yanliang Liu, Chaosong Gao, Dong Li, Xin Zhang, Jiongtao Zhu, Meng Wu, Wenjun Liu, Tongyu Shi, Xingchen He, Jiahong Wang, Hao Huang, Zonghai Sheng, Dong Liang, Xue-Feng Yu, Hairong Zheng, Xiangming Sun, Yongshuai Ge
Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-7 (2024)
Abstract High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-life
Externí odkaz: https://doaj.org/article/0715b9b1f08e4eeba7110e09ca5ae3d4
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2
Akademický článek
PbI2‐DMSO Assisted In Situ Growth of Perovskite Wafers for Sensitive Direct X‐Ray Detection
Autor: Wenjun Liu, Tongyu Shi, Jiongtao Zhu, Zhenyu Zhang, Dong Li, Xingchen He, Xiongsheng Fan, Lingqiang Meng, Jiahong Wang, Rui He, Yongshuai Ge, Yanliang Liu, Paul K. Chu, Xue‐Feng Yu
Publikováno v: Advanced Science, Vol 10, Iss 1, Pp n/a-n/a (2023)
Abstract Although perovskite wafers with a scalable size and thickness are suitable for direct X‐ray detection, polycrystalline perovskite wafers have drawbacks such as the high defect density, defective grain boundaries, and low crystallinity. Her
Externí odkaz: https://doaj.org/article/4b6d0b430eaa4b24b329fac0dc9df8c6
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6
PbI
Autor: Wenjun, Liu, Tongyu, Shi, Jiongtao, Zhu, Zhenyu, Zhang, Dong, Li, Xingchen, He, Xiongsheng, Fan, Lingqiang, Meng, Jiahong, Wang, Rui, He, Yongshuai, Ge, Yanliang, Liu, Paul K, Chu, Xue-Feng, Yu
Publikováno v: Advanced science (Weinheim, Baden-Wurttemberg, Germany).
Although perovskite wafers with a scalable size and thickness are suitable for direct X-ray detection, polycrystalline perovskite wafers have drawbacks such as the high defect density, defective grain boundaries, and low crystallinity. Herein, PbI
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::2adbb3d4a36ebe05ffa4b7a3abe8c606
https://pubmed.ncbi.nlm.nih.gov/36372541
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8
ADAPTIVE-NET: deep computed tomography reconstruction network with analytical domain transformation knowledge
Autor: Hu Zhanli, Yongshuai Ge, Qiyang Zhang, Dong Liang, Jianwei Chen, Jiongtao Zhu, Hairong Zheng, Ting Su, Xiaolei Deng
Publikováno v: Quantitative Imaging in Medicine and Surgery. 10:415-427
Background: Recently, the paradigm of computed tomography (CT) reconstruction has shifted as the deep learning technique evolves. In this study, we proposed a new convolutional neural network (called ADAPTIVE-NET) to perform CT image reconstruction d
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8e91c52a341cdb14e596a501051c9e0
https://doi.org/10.21037/qims.2019.12.12
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9
Performance evaluation of dual-energy CT and differential phase contrast CT in quantitative imaging applications
Autor: Xin Zhang, Ting Su, Jiecheng Yang, Jiongtao Zhu, Dongmei Xia, Hairong Zheng, Dong Liang, Yongshuai Ge
Publikováno v: Medical physicsREFERENCES. 49(2)
The purpose of this study is to evaluate and compare the quantitative material decomposition performance of the dual-energy CT (DECT) and differential phase contrast CT (DPCT) via numerical observer studies.The electron density (The model observer re
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::001b47844fc6377ea439f205783fe000
https://pubmed.ncbi.nlm.nih.gov/34951037
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