Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

Volumn 17, Issue , 2014, Pages 438-445

  Maier Hein, Lena ^a   Mersmann, Sven ^a   Kondermann, Daniel ^a   Bodenstedt, Sebastian ^a   Sanchez, Alexandro ^a   Stock, Christian ^a   Kenngott, Hannes G otz ^a   Eisenmann, Mathias ^a   Speidel, Stefanie ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CROWDSOURCING; DEVICE FAILURE ANALYSIS; DEVICES; EQUIPMENT DESIGN; HUMAN; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; LAPAROSCOPE; LAPAROSCOPY; OBSERVER VARIATION; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CROWDSOURCING; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; HUMANS; IMAGE ENHANCEMENT; INFORMATION STORAGE AND RETRIEVAL; LAPAROSCOPES; LAPAROSCOPY; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84922277898     PISSN: None     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (0)