Vertebrae localization in pathological spine CT via dense classification from sparse annotations

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 262-270

  Glocker, Ben ^a   Zikic, Darko ^a   Konukoglu, Ender ^b   Haynor, David R ^c   Criminisi, Antonio ^a  

^a MICROSOFT RESEARCH   (United Kingdom)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IDENTIFICATION RATES; INTENSITY FEATURES; LOCALIZATION AND IDENTIFICATION; LOCALIZATION ERRORS; PARAMETRIC MODELING; QUANTITATIVE EVALUATION; SUPERVISED CLASSIFICATION; SURGICAL PLANNING;

ALGORITHMS; MODELS; PATHOLOGY; STATISTICAL TESTS;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE QUALITY; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SCOLIOSIS; SENSITIVITY AND SPECIFICITY; SPINE;

ALGORITHMS; HUMANS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SCOLIOSIS; SENSITIVITY AND SPECIFICITY; SPINE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84885908791     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40763-5_33     Document Type: Conference Paper

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