Active learning for convenient annotation and classification of secondary ion mass spectrometry images

Analytical Chemistry

Volumn 85, Issue 1, 2013, Pages 147-155

  Hanselmann, Michael ^a   Röder, Jens ^a,b   Köthe, Ullrich ^a   Renard, Bernhard Y ^c   Heeren, Ron M A ^d   Hamprecht, Fred A ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b ROBERT BOSCH GMBH   (Germany)

^c ROBERT KOCH INSTITUTE   (Germany)

^d FOM INSTITUTE AMOLF   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CANDIDATE PIXELS; CLASSIFICATION ACCURACY; DIGITAL STAINING; MULTI-CLASS; RANDOM FOREST CLASSIFIER; RANDOM FORESTS; RANDOM SAMPLING; SECONDARY IONS;

DECISION TREES; PIXELS; SECONDARY ION MASS SPECTROMETRY; SUPPORT VECTOR MACHINES; TISSUE;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; ANIMAL; ARTICLE; AUTOMATED PATTERN RECOGNITION; CELL STRAIN MCF 7; HUMAN; MASS SPECTROMETRY; MOUSE; SUPPORT VECTOR MACHINE; XENOGRAFT;

ALGORITHMS; ANIMALS; HUMANS; MCF-7 CELLS; MICE; PATTERN RECOGNITION, AUTOMATED; SPECTROMETRY, MASS, SECONDARY ION; SUPPORT VECTOR MACHINES; TRANSPLANTATION, HETEROLOGOUS;

EID: 84871761513     PISSN: 00032700     EISSN: 15206882     Source Type: Journal    
DOI: 10.1021/ac3023313     Document Type: Article

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