Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

Zhehui Wang, Xin Yue, Shanny Lin, Wenting Li, B. Wolfe, S. Clayton, M. Makela, Chris Morris, S. Spannagel, E. Ramberg, J. Estrada, Hao Zhu, Jifeng Liu, E. Fossum
{"title":"Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography","authors":"Zhehui Wang, Xin Yue, Shanny Lin, Wenting Li, B. Wolfe, S. Clayton, M. Makela, Chris Morris, S. Spannagel, E. Ramberg, J. Estrada, Hao Zhu, Jifeng Liu, E. Fossum","doi":"10.22323/1.420.0041","DOIUrl":null,"url":null,"abstract":"We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.","PeriodicalId":275608,"journal":{"name":"Proceedings of 10th International Workshop on Semiconductor Pixel Detectors for Particles and Imaging — PoS(Pixel2022)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 10th International Workshop on Semiconductor Pixel Detectors for Particles and Imaging — PoS(Pixel2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22323/1.420.0041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于多模态射线成像和断层扫描的超快CMOS图像传感器和数据支持的超分辨率
我们总结了近年来在超快CMOS图像传感器的发展和应用神经网络后处理CMOS和电荷耦合器件(CCD)图像数据,以达到亚像素分辨率(因此$super$-$resolution$)。新颖的CMOS像素设计和数据支持的图像后处理相结合,为超高速高分辨率多模态射线成像和断层扫描应用提供了一条有前途的道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Silicon detectors for precision track timing Preface to the Proceedings of PIXEL2022 Simulation Study of Pulse Height Difference Between Pixel Patterns of X-ray CCDs Onboard the XRISM Satellite Hadron Damage Investigation of FBK and HPK Low Gain Avalanche Detectors Characterization of Hybrid Pixel Detector With CdTe Sensor
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1