Atlas encoding by randomized forests for efficient label propagation

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

Volumn 8151 LNCS, Issue PART 3, 2013, Pages 66-73

  Zikic, Darko ^a   Glocker, Ben ^a   Criminisi, Antonio ^a  

^a MICROSOFT RESEARCH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; DEEP CLASSIFICATIONS; LABEL PROPAGATION; LARGE DATABASE; PROBABILISTIC ATLAS; STATE OF THE ART; TARGET IMAGES; TEST TIME; LINEAR REGISTRATION;

ENCODING (SYMBOLS); EXPERIMENTS; IMAGE FUSION; FORESTRY; MEDICAL COMPUTING; MEDICAL IMAGING;

FORESTRY; IMAGE FUSION;

EXPERIMENTATION; FORESTRY; IMAGE ANALYSIS; SYMBOLS; CLASSIFICATION; COSTS; FORESTS;

ALGORITHM; ARTICLE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STAINING; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MAGNETIC RESONANCE IMAGING; MODELS, ANATOMIC; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STAINING AND LABELING; SUBTRACTION TECHNIQUE;

EID: 84885942673     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40760-4_9     Document Type: Conference Paper

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