Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data

Cell Systems

Volumn 4, Issue 6, 2017, Pages 651-655.e5

  Piccinini, Filippo ^a   Balassa, Tamas ^b   Szkalisity, Abel ^b   Molnar, Csaba ^b   Paavolainen, Lassi ^c   Kujala, Kaisa ^c   Buzas, Krisztina ^b,d   Sarazova, Marie ^e   Pietiainen, Vilja ^c   Kutay, Ulrike ^e   Smith, Kevin ^f,g   Horvath, Peter ^b,c  

^a DEPARTMENT OF MEDICAL ONCOLOGY   (Italy)

^b INSTITUTE OF EXPERIMENTAL MEDICINE   (Hungary)

^c UNIVERSITY OF HELSINKI   (Finland)

^d UNIVERSITY OF SZEGED   (Hungary)

^e ETH ZURICH   (Switzerland)

^f ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^g SCIENCE FOR LIFE LABORATORY   (Sweden)

Author keywords

cell classification; fluorescence microscopy; high content screening; image processing; machine learning; multi parametric analysis; oncology; open source software; phenotypic discovery; single cell analysis

Indexed keywords

ACCURACY; ARTICLE; IMAGE ANALYSIS; IMAGING; MACHINE LEARNING; MICROSCOPY; PHENOTYPE; PRIORITY JOURNAL; SOFTWARE; CELL LINE; HUMAN; IMAGE PROCESSING; PROCEDURES;

CELL LINE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MACHINE LEARNING; MICROSCOPY; PHENOTYPE; SOFTWARE;

EID: 85020911088     PISSN: 24054712     EISSN: 24054720     Source Type: Journal    
DOI: 10.1016/j.cels.2017.05.012     Document Type: Article

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