Focusing light through scattering media by reinforced hybrid algorithms
Light scattering inside disordered media poses a significant challenge to achieve deep depth and high resolution simultaneously in biomedical optical imaging. Wavefront shaping emerged recently as one of the most potential methods to tackle this problem. So far, numerous algorithms have been reporte...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2020-01-01
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| Series: | APL Photonics |
| Online Access: | http://dx.doi.org/10.1063/1.5131181 |
| _version_ | 1828155666053726208 |
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| author | Yunqi Luo Suxia Yan Huanhao Li Puxiang Lai Yuanjin Zheng |
| author_facet | Yunqi Luo Suxia Yan Huanhao Li Puxiang Lai Yuanjin Zheng |
| author_sort | Yunqi Luo |
| collection | DOAJ |
| description | Light scattering inside disordered media poses a significant challenge to achieve deep depth and high resolution simultaneously in biomedical optical imaging. Wavefront shaping emerged recently as one of the most potential methods to tackle this problem. So far, numerous algorithms have been reported, while each has its own pros and cons. In this article, we exploit a new thought that one algorithm can be reinforced by another complementary algorithm since they effectively compensate each other’s weaknesses, resulting in a more efficient hybrid algorithm. Herein, we introduce a systematical approach named GeneNN (Genetic Neural Network) as a proof of concept. Preliminary light focusing has been achieved by a deep neural network, whose results are fed to a genetic algorithm as an initial condition. The genetic algorithm furthers the optimization, evolving to converge into the global optimum. Experimental results demonstrate that with the proposed GeneNN, optimization speed is almost doubled and wavefront shaping performance can be improved up to 40% over conventional methods. The reinforced hybrid algorithm shows great potential in facilitating various biomedical and optical imaging techniques. |
| first_indexed | 2024-04-11T22:57:05Z |
| format | Article |
| id | doaj.art-2085345c81674f5b90b076dd2bbd4b5f |
| institution | Directory Open Access Journal |
| issn | 2378-0967 |
| language | English |
| last_indexed | 2024-04-11T22:57:05Z |
| publishDate | 2020-01-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | APL Photonics |
| spelling | doaj.art-2085345c81674f5b90b076dd2bbd4b5f2022-12-22T03:58:20ZengAIP Publishing LLCAPL Photonics2378-09672020-01-0151016109016109-1210.1063/1.5131181Focusing light through scattering media by reinforced hybrid algorithmsYunqi Luo0Suxia Yan1Huanhao Li2Puxiang Lai3Yuanjin Zheng4School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798Department of Biomedical Engineering, Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Biomedical Engineering, Hong Kong Polytechnic University, Hong Kong, ChinaSchool of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798Light scattering inside disordered media poses a significant challenge to achieve deep depth and high resolution simultaneously in biomedical optical imaging. Wavefront shaping emerged recently as one of the most potential methods to tackle this problem. So far, numerous algorithms have been reported, while each has its own pros and cons. In this article, we exploit a new thought that one algorithm can be reinforced by another complementary algorithm since they effectively compensate each other’s weaknesses, resulting in a more efficient hybrid algorithm. Herein, we introduce a systematical approach named GeneNN (Genetic Neural Network) as a proof of concept. Preliminary light focusing has been achieved by a deep neural network, whose results are fed to a genetic algorithm as an initial condition. The genetic algorithm furthers the optimization, evolving to converge into the global optimum. Experimental results demonstrate that with the proposed GeneNN, optimization speed is almost doubled and wavefront shaping performance can be improved up to 40% over conventional methods. The reinforced hybrid algorithm shows great potential in facilitating various biomedical and optical imaging techniques.http://dx.doi.org/10.1063/1.5131181 |
| spellingShingle | Yunqi Luo Suxia Yan Huanhao Li Puxiang Lai Yuanjin Zheng Focusing light through scattering media by reinforced hybrid algorithms APL Photonics |
| title | Focusing light through scattering media by reinforced hybrid algorithms |
| title_full | Focusing light through scattering media by reinforced hybrid algorithms |
| title_fullStr | Focusing light through scattering media by reinforced hybrid algorithms |
| title_full_unstemmed | Focusing light through scattering media by reinforced hybrid algorithms |
| title_short | Focusing light through scattering media by reinforced hybrid algorithms |
| title_sort | focusing light through scattering media by reinforced hybrid algorithms |
| url | http://dx.doi.org/10.1063/1.5131181 |
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