Augmenting auto-context with global geometric features for spinal cord segmentation

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

Volumn 8184 LNCS, Issue , 2013, Pages 211-218

  Kawahara, Jeremy ^a   McIntosh, Chris ^a,b   Tam, Roger ^c   Hamarneh, Ghassan ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

^b PRINCESS MARGARET HOSPITAL   (Canada)

^c UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

MEDICAL IMAGING;

ANATOMICAL SHAPE; GEOMETRIC FEATURE; GLOBAL SCALE; HIGH LEVEL KNOWLEDGE; HIGH-LEVEL RULES; MULTIPLE SCLEROSIS; SPINAL CORDS; STATE-OF-THE-ART METHODS;

LEARNING SYSTEMS;

EID: 84886733311     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-02267-3_27     Document Type: Conference Paper

References (11)

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