In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images

Cell

Volumn 173, Issue 3, 2018, Pages 792-803.e19

  Christiansen, Eric M ^a   Yang, Samuel J ^a   Ando, D Michael ^a   Javaherian, Ashkan ^b   Skibinski, Gaia ^b   Lipnick, Scott ^c,d,h   Mount, Elliot ^b   O'Neil, Alison ^c   Shah, Kevan ^b   Lee, Alicia K ^b   Goyal, Piyush ^b   Fedus, William ^a,f   Poplin, Ryan ^a   Esteva, Andre ^a,g   Berndl, Marc ^a   Rubin, Lee L ^c   Nelson, Philip ^a   Finkbeiner, Steven ^b,e  

^a GOOGLE INC   (United States)

^b GLADSTONE INSTITUTES   (United States)

^c Harvard University   (United States)

^d HARVARD MEDICAL SCHOOL   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f UNIVERSITÉ DE MONTRÉAL   (Canada)

^g Stanford University   (United States)

^h MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

cancer; computer vision; deep learning; machine learning; microscopy; neuroscience; stem cells

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL DEATH; CELL LABELING; CELL NUCLEUS; CELL VIABILITY; CELLS BY BODY ANATOMY; CHEMICAL LABELING; COMPUTER MODEL; FACTUAL DATABASE; FLUORESCENCE ANALYSIS; FLUORESCENCE MICROSCOPY; IN SILICO LABELING; PREDICTION; PREDICTIVE VALUE; PRIORITY JOURNAL; TRANSFER OF LEARNING; WORKFLOW; ANIMAL; BRAIN CORTEX; CELL SURVIVAL; CHEMISTRY; CYTOLOGY; HUMAN; IMAGE PROCESSING; INDUCED PLURIPOTENT STEM CELL; MACHINE LEARNING; MOTONEURON; NEUROSCIENCE; PROCEDURES; RAT; SOFTWARE; STEM CELL; TUMOR CELL LINE;

FLUORESCENT DYE;

ALGORITHMS; ANIMALS; CELL LINE, TUMOR; CELL SURVIVAL; CEREBRAL CORTEX; FLUORESCENT DYES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INDUCED PLURIPOTENT STEM CELLS; MACHINE LEARNING; MICROSCOPY, FLUORESCENCE; MOTOR NEURONS; NEURAL NETWORKS (COMPUTER); NEUROSCIENCES; RATS; SOFTWARE; STEM CELLS;

EID: 85043779029     PISSN: 00928674     EISSN: 10974172     Source Type: Journal    
DOI: 10.1016/j.cell.2018.03.040     Document Type: Article

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