Agreement-based semi-supervised learning for skull stripping

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

Volumn 6363 LNCS, Issue PART 3, 2010, Pages 147-154

  Iglesias, Juan Eugenio ^a   Liu, Cheng Yi ^a   Thompson, Paul ^a   Tu, Zhuowen ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN MRI; DATA SETS; GROUND TRUTH; LEARNING-BASED APPROACH; MRI SCAN; RANDOM FOREST CLASSIFIER; SEMI-SUPERVISED LEARNING; SKULL STRIPPING; STATE-OF-THE-ART SYSTEM; TEST IMAGES; TRAINING DATA; UNLABELED DATA;

CLASSIFIERS; DECISION TREES; LEARNING ALGORITHMS; MEDICAL COMPUTING; SUPERVISED LEARNING;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; SKULL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SKULL; SUBTRACTION TECHNIQUE;

EID: 84883842344     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15711-0_19     Document Type: Conference Paper

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