Author Affiliations
Abstract
1 School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China
2 MIIT Key Laboratory of Advanced Solid Laser, Nanjing University of Science and Technology, Nanjing 210094, China
3 Department of Material Science and Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA
Currently, it is generally known that lens-free holographic microscopy, which has no imaging lens, can realize a large field-of-view imaging with a low-cost setup. However, in order to obtain colorful images, traditional lens-free holographic microscopy should utilize at least three quasi-chromatic light sources of discrete wavelengths, such as red LED, green LED, and blue LED. Here, we present a virtual colorization by deep learning methods to transfer a gray lens-free microscopy image into a colorful image. Through pairs of images, i.e., grayscale lens-free microscopy images under green LED at 550 nm illumination and colorful bright-field microscopy images, a generative adversarial network (GAN) is trained, and its effectiveness of virtual colorization is proved by applying it to hematoxylin and eosin stained pathological tissue samples imaging. Our computational virtual colorization method might strengthen the monochromatic illumination lens-free microscopy in medical pathology applications and label staining biomedical research.
lens-free microscopy deep learning digital holography virtual colorization Chinese Optics Letters
2020, 18(12): 121705
1 北京大学工学院生物医学工程系, 北京100871
2 北京大学人民医院乳腺中心, 北京100044
无透镜显微成像(lens-free microscopy)是一种在不借助透镜的情况下进行成像的技术。它基于Gabor同轴全息原理, 利用面阵探测器采集原始全息图, 随后通过数字图像处理技术重建样本, 从而实现数字显微成像。像素超分辨技术缩小了等效像素, 提供更多细节信息使得再现像的分辨率得以直接提升, 而且多种相位恢复手段通过去除孪生像也达到了间接提高分辨率的目的, 尤其是对密集样本。无透镜显微成像技术突破了传统光学显微镜由透镜带来的空间带宽积的限制, 实现了大视野范围下的高分辨率成像, 因此, 这一技术能够提供大视场下的临床样本快速诊断和准确检测。另外, 新兴的算法和硬件都在不断地加快数据采集和计算速度, 扩展了其在高速运动样本和纳米尺度样本上的应用。最近无透镜技术和其配套硬件设备发展方向趋向于硬件紧凑、算法密集、实时、三维、彩色、高分辨率的便携式分立器件或配件。
无透镜显微术 同轴全息术 相位恢复 像素超分辨 lens-free microscopy in-line holography phase recovery pixel super-resolution
