显微镜
免疫荧光
反射率
光学显微镜
计算机科学
人工智能
虚拟显微镜
光学
材料科学
生物
物理
扫描电子显微镜
抗体
免疫学
作者
Shiyi Cheng,Sipei Fu,Yumi Mun Kim,Ji Yi,Lei Tian
标识
DOI:10.1109/ipc47351.2020.9252556
摘要
To circumvent the limitations of conventional immunofluorescence (IF) microscopy, a deep learning approach is proposed for transforming morphological information contained in reflectance microscopy to specific and accurate IF prediction with high multiplexing capability.
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