A 4D statistical shape model for automated segmentation of lungs with large tumors

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

Volumn 7511 LNCS, Issue , 2012, Pages 347-354

  Wilms, Matthias ^a   Ehrhardt, Jan ^a   Handels, Heinz ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ORGANS; COMPUTERIZED TOMOGRAPHY; GRAPHIC METHODS; MEDICAL COMPUTING; MEDICAL IMAGING; TUMORS;

AUTOMATED SEGMENTATION; LUNG SEGMENTATION; MODEL-BASED SEGMENTATION; SEGMENTATION RESULTS; STATISTICAL SHAPE MODEL; TEMPORAL COHERENCE; TEMPORAL INFORMATION; TIME-CONSUMING TASKS;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER SIMULATION; HUMAN; IMAGE QUALITY; LUNG TUMOR; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; RESPIRATORY GATED IMAGING; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGING, THREE-DIMENSIONAL; LUNG NEOPLASMS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; RESPIRATORY-GATED IMAGING TECHNIQUES; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84988867593     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33418-4_43     Document Type: Conference Paper

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