Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach
This study developed a novel dual-wavelength confocal laser speckle imaging platform. The system includes both visible and near-infrared lasers and two imaging modes: confocal and wide-field laser speckle contrast imaging. The experimental results confirm that the proposed system can be used to meas...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/11/11/1085 |
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| author | E Du Haohan Zheng Honghui He Shiguo Li Cong Qiu Weifeng Zhang Guoqing Wang Xingquan Li Lan Ma Shuhao Shen Yuan Zhou |
| author_facet | E Du Haohan Zheng Honghui He Shiguo Li Cong Qiu Weifeng Zhang Guoqing Wang Xingquan Li Lan Ma Shuhao Shen Yuan Zhou |
| author_sort | E Du |
| collection | DOAJ |
| description | This study developed a novel dual-wavelength confocal laser speckle imaging platform. The system includes both visible and near-infrared lasers and two imaging modes: confocal and wide-field laser speckle contrast imaging. The experimental results confirm that the proposed system can be used to measure not only blood flow but also blood oxygen saturation. Additionally, we proposed a blood flow perfusion imaging method called BlingNet (a blood flow imaging CNN) based on the laser speckle contrast imaging technique and deep learning approach. Compared to the traditional nonlinear fitting method, this method has superior accuracy and robustness with higher imaging speed, making real-time blood flow imaging possible. |
| format | Article |
| id | doaj-art-13f58d5433bc40a195ed8bc4039d396d |
| institution | OA Journals |
| issn | 2304-6732 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj-art-13f58d5433bc40a195ed8bc4039d396d2025-08-20T01:54:03ZengMDPI AGPhotonics2304-67322024-11-011111108510.3390/photonics11111085Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning ApproachE Du0Haohan Zheng1Honghui He2Shiguo Li3Cong Qiu4Weifeng Zhang5Guoqing Wang6Xingquan Li7Lan Ma8Shuhao Shen9Yuan Zhou10School of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaSchool of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaSchool of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaSchool of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaSchool of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaSchool of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, ChinaGuangzhou Institute of Technology, Xidian University, Guangzhou 510555, ChinaGuangzhou Institute of Technology, Xidian University, Guangzhou 510555, ChinaShenzhen Stomatological Hospital, Southern Medical University, Shenzhen 518005, ChinaThis study developed a novel dual-wavelength confocal laser speckle imaging platform. The system includes both visible and near-infrared lasers and two imaging modes: confocal and wide-field laser speckle contrast imaging. The experimental results confirm that the proposed system can be used to measure not only blood flow but also blood oxygen saturation. Additionally, we proposed a blood flow perfusion imaging method called BlingNet (a blood flow imaging CNN) based on the laser speckle contrast imaging technique and deep learning approach. Compared to the traditional nonlinear fitting method, this method has superior accuracy and robustness with higher imaging speed, making real-time blood flow imaging possible.https://www.mdpi.com/2304-6732/11/11/1085laser speckleblood flowhemoglobin oxygen saturationconfocaldeep learning |
| spellingShingle | E Du Haohan Zheng Honghui He Shiguo Li Cong Qiu Weifeng Zhang Guoqing Wang Xingquan Li Lan Ma Shuhao Shen Yuan Zhou Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach Photonics laser speckle blood flow hemoglobin oxygen saturation confocal deep learning |
| title | Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach |
| title_full | Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach |
| title_fullStr | Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach |
| title_full_unstemmed | Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach |
| title_short | Dual-Wavelength Confocal Laser Speckle Contrast Imaging Using a Deep Learning Approach |
| title_sort | dual wavelength confocal laser speckle contrast imaging using a deep learning approach |
| topic | laser speckle blood flow hemoglobin oxygen saturation confocal deep learning |
| url | https://www.mdpi.com/2304-6732/11/11/1085 |
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