Cytopathological image analysis using deep-learning networks in microfluidic microscopy

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 34, Issue 1, 2017, Pages 111-121

  Gopakumar, G ^a   Babu, K Hari ^a   Mishra, Deepak ^a   Gorthi, Sai Siva ^b   Subrahmanyam, Gorthi R K Sai ^a  

^a INDIAN INSTITUTE OF SPACE SCIENCE AND TECHNOLOGY   (India)

^b INDIAN INSTITUTE OF SCIENCE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

CELL CULTURE; CELLS; CYTOLOGY; DIAGNOSIS; DISEASES; FEATURE EXTRACTION; IMAGING TECHNIQUES; LEARNING ALGORITHMS; LEARNING SYSTEMS; NETWORK ARCHITECTURE; NEURAL NETWORKS; PERSONNEL TRAINING; THROUGHPUT;

CONVOLUTIONAL NEURAL NETWORK; DECISION SYSTEMS; DEEP BELIEF NETWORKS; DISEASE SCREENING; FINE SEGMENTATIONS; HIGH THROUGHPUT; HIGH THROUGHPUT CELL IMAGING; HUMAN EXPERTISE;

MICROFLUIDICS;

ACUTE LYMPHOBLASTIC LEUKEMIA; ALGORITHM; ARTIFICIAL NEURAL NETWORK; HL-60 CELL LINE; HUMAN; IMAGE PROCESSING; K-562 CELL LINE; MACHINE LEARNING; MICROFLUIDICS; MICROSCOPY; PATHOLOGY; PROCEDURES;

ALGORITHMS; HL-60 CELLS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; K562 CELLS; MACHINE LEARNING; MICROFLUIDICS; MICROSCOPY; NEURAL NETWORKS (COMPUTER); PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA;

EID: 85009237688     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.34.000111     Document Type: Article

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