Automatic detection and segmentation of axillary lymph nodes

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

Volumn 6361 LNCS, Issue PART 1, 2010, Pages 28-36

  Barbu, Adrian ^a   Suehling, Michael ^b   Xu, Xun ^b   Liu, David ^b   Zhou, S Kevin ^b   Comaniciu, Dorin ^b  

^a FLORIDA STATE UNIVERSITY   (United States)

^b SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC DETECTION; AVERAGE RUNNING TIME; AXILLARY LYMPH NODES; CANCER TREATMENT; COMPUTED TOMOGRAPHY DATA; DETECTION RATES; EFFECTIVE LEARNING; FALSE POSITIVE; LEARNING-BASED APPROACH; LOCAL GRADIENTS; LYMPH NODE; MARGINAL SPACE LEARNING; SEGMENTATION METHODS; SEGMENTATION RESULTS; SELF-ALIGNING;

COMPUTERIZED TOMOGRAPHY; MEDICAL COMPUTING; MEDICAL IMAGING;

BODY FLUIDS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; AXILLA; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE QUALITY; LYMPH NODE; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AXILLA; HUMANS; IMAGING, THREE-DIMENSIONAL; LYMPH NODES; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 78349235407     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15705-9_4     Document Type: Conference Paper

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