Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/94365
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Biomedical Engineering | en_US |
dc.contributor | Mainland Development Office | en_US |
dc.creator | Luo, Y | en_US |
dc.creator | Li, H | en_US |
dc.creator | Zhang, R | en_US |
dc.creator | Lai, P | en_US |
dc.creator | Zheng, Y | en_US |
dc.date.accessioned | 2022-08-12T03:04:34Z | - |
dc.date.available | 2022-08-12T03:04:34Z | - |
dc.identifier.issn | 0277-786X | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/94365 | - |
dc.description | SPIE BIOS, 2-7 February 2019, San Francisco, California, United States | en_US |
dc.language.iso | en | en_US |
dc.publisher | SPIE-International Society for Optical Engineering | en_US |
dc.rights | Copyright 2019 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. | en_US |
dc.rights | The following publication Luo, Y., Li, H., Zhang, R., Lai, P., & Zheng, Y. (2019). Deep learning assisted optical wavefront shaping in disordered medium. Adaptive Optics and Wavefront Control for Biological Systems V, Proceedings, 10886, 1088612 is available at https://doi.org/10.1117/12.2504425 | en_US |
dc.subject | Convolutional neural network | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Focusing | en_US |
dc.subject | Wavefront shaping | en_US |
dc.title | Deep learning assisted optical wavefront shaping in disordered medium | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.volume | 10886 | en_US |
dc.identifier.doi | 10.1117/12.2504425 | en_US |
dcterms.abstract | Wavefront shaping (WFS) has been put forward several years ago to break the limitation caused by optical scattering in inhomogeneous medium, and realize optical focusing in disordered medium like biological tissues. However, usually, with traditional methods, WFS is time consuming and not cost efficient since it requires long time to obtain the information of the scattering medium. Here we propose the deep learning assisted wavefront shaping, which uses deep neural networks to predict the desired input optical modes that are needed to realize focusing after light passes through a scattering medium. Simulation results show that the pre-trained neural network is able to map output optical modes to input modes. Compared with previous methods which use iterative optimization, our method realizes a focused speckle pattern with the help of deep learning, which will definitely reduce complexity and time spent in optimization. Experiments will be conducted soon. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Proceedings of SPIE : the International Society for Optical Engineering, 2019, v. 10886, 1088612 | en_US |
dcterms.isPartOf | Proceedings of SPIE : the International Society for Optical Engineering | en_US |
dcterms.issued | 2019-02 | - |
dc.identifier.scopus | 2-s2.0-85066622575 | - |
dc.relation.conference | SPIE BIOS | en_US |
dc.identifier.eissn | 1996-756X | en_US |
dc.identifier.artn | 1088612 | en_US |
dc.description.validate | 202208 bcfc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | BME-0129 | - |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 14782303 | - |
dc.description.oaCategory | VoR allowed | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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Li_Deep_Learning_Assisted.pdf | 916.74 kB | Adobe PDF | View/Open |
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