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

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8674 LNCS, Issue PART 2, 2014, Pages 438-445

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

^a GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^b UNIVERSITY OF HEIDELBERG   (Germany)

^c KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; ENDOSCOPY; LEARNING ALGORITHMS; ALGORITHMS; COMPUTER AIDED INSTRUCTION; DATA HANDLING; IMAGE PROCESSING; IMAGE SEGMENTATION; LEARNING SYSTEMS; MEDICAL COMPUTING;

COMPUTER ASSISTED; ENDOSCOPIC IMAGE; HIGHLY ACCURATE; IMAGE CLASSIFIERS; MEDICAL EXPERTS; MEDICAL INSTRUMENTS; ON-LINE COMMUNITIES; SCIENTIFIC COMMUNITY;

IMAGE SEGMENTATION; MEDICAL IMAGING;

EID: 84906971515     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10470-6_55     Document Type: Conference Paper

References (11)

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