Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network

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

Volumn 8150 LNCS, Issue PART 2, 2013, Pages 246-253

  Prasoon, Adhish ^a   Petersen, Kersten ^a   Igel, Christian ^a   Lauze, François ^a   Dam, Erik ^b   Nielsen, Mads ^a,b  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b Biomediq ^*  (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMICAL STRUCTURES; CARTILAGE SEGMENTATION; CLASSIFICATION APPROACH; CONVOLUTIONAL NEURAL NETWORK; DEEP FEATURE LEARNING; HIERARCHICAL REPRESENTATION; STATE-OF-THE-ART METHODS; VOXEL CLASSIFICATIONS;

CARTILAGE; THREE DIMENSIONAL;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTICULAR CARTILAGE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; KNEE; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; CARTILAGE, ARTICULAR; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; KNEE JOINT; MAGNETIC RESONANCE IMAGING; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84885933775     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40763-5_31     Document Type: Conference Paper

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