High-throughput deep learning microscopy using multi-angle super-resolution

Jizhou Zhang, Tingfa Xu, Xiangmin Li, Yizhou Zhang, Yiwen Chen, Xin Wang, Shushan Wang, Cheng Wang
2020 IEEE Photonics Journal  
Biomedical applications such as pathology and hematology expect microscopes with high space-bandwidth product (SBP) which is difficult to achieve with conventional microscope setup. By applying a deep neural network, we demonstrate a high spacebandwidth product microscopic technique termed multi-angle super-resolution microscopy (MASRM) to achieve high-resolution imaging with the low-magnification objective. We design a multiple-branch deep residual network which extracts high-frequency
more » ... ion and color information in obliquely-illuminated low-resolution input images and generates high-resolution output. To train our network, we build a well-registered dataset in which both low-resolution input and high-resolution target are real captured images. We carry out detailed experiments to demonstrate the effectiveness of MASRM and compare it with a computational imaging technique termed Fourier ptychographic microscopy (FPM). This data-driven technique unleashes the potential of traditional microscopes with low cost and has broad prospects in biomedical applications.
doi:10.1109/jphot.2020.2977888 fatcat:vssmd6psbfehtkqfrlctxhriqy