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Digital staining in optical microscopy using deep learning-a review

PhotoniX 2023年第1期4卷 64-95页

作者： Lucas Kreiss Shaowei Jiang Xiang Li Shiqi Xu Kevin C.Zhou Kyung Chul Lee Alexander Mühlberg Kanghyun Kim Amey Chaware Michael Ando Laura Barisoni Seung Ah Lee Guoan Zheng Kyle J.Lafata Oliver Friedrich Roarke horstmeyer Department of Biomedical engineering Duke UniversityDurhamNC 27708USA Institute of Medical Biotechnology Friedrich-Alexander University(FAU)ErlangenGermany Department of Biomedical engineering University of ConnecticutMansfieldConnecticutUSA Department of Radiation Physics Duke UniversityDurhamNC 27708USA Department of electrical engineering&Computer Sciences University of CaliforniaBerkeleyCAUSA School of electrical&electronic engineering Yonsei UniversitySeoul 03722Republic of Korea Google Inc.Mountain ViewCA 94043USA Department of Pathology Duke UniversityDurhamNC 27708USA

Until recently,conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics,fundamental research and *** this role as gold-standard,staining protocols face several challenges,such as a need for extensive,manual processing of samples,substantial time delays,altered tissue homeostasis,limited choice of contrast agents,2D imaging instead of 3D tomography and many ***-free optical technologies,on the other hand,do not rely on exogenous and artificial markers,by exploiting intrinsic optical contrast mechanisms,where the specificity is typically less obvious to the human *** the past few years,digital staining has emerged as a promising concept to use modern deep learning for the translation from optical contrast to established biochemical contrast of actual *** this review article,we provide an in-depth analysis of the current state-of-the-art in this field,suggest methods of good practice,identify pitfalls and challenges and postulate promising advances towards potential future implementations and applications.

关键词： Deep learning Digital staining Optical microscopy Virtual staining In-silica pseudo-h&e Virtual fluorescence Generative models Image translation

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