Portable deep learning singlet microscope

被引:10
|
作者
Shen, Hua [1 ,2 ]
Gao, Jinming [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing 210094, Peoples R China
[2] Univ Calif Los Angeles, Dept Mat Sci & Engn, Los Angeles, CA 90024 USA
基金
中国国家自然科学基金;
关键词
aspheric lens; biologic imaging; computational imaging; optical design; singlet microscopy; GRADIENT-INDEX; WIDE-FIELD; SYSTEM;
D O I
10.1002/jbio.202000013
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Having the least lenses, the significant feature of the singlet imaging system, helps the development of the portable and cost-effective microscopes. A novel method of monochromatic/color singlet microscopy, which is combined with only one aspheric lens and deep learning computational imaging technology, is proposed in this article. The designed singlet aspheric lens is an approximate linear signal system, which means modulation-transfer-function curves on all field-of-views (5 mm diagonally) are almost coincident with each other. The purpose of the designed linear signal system is to further improve the resolution of our microscope by using deep learning algorithm. As a proof of concept, we designed a singlet microscopy based on our method, which weighs only 400 g. The experimental data and results of the sample USAF-1951 target and bio-sample (the Equisetum-arvense Strobile L.S), prove that the performance of the proposed singlet microscope is competitive to a commercial microscope with the 4X/NA0.1 objective lens. We believe that our idea and method would guide to design more cost-effective and powerful singlet imaging system.
引用
收藏
页数:10
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