Automated 3-D segmentation of lungs with lung cancer in CT data using a novel robust active shape model approach

IEEE Transactions on Medical Imaging

Volumn 31, Issue 2, 2012, Pages 449-460

  Sun, Shanhui ^a   Bauer, Christian ^a   Beichel, Reinhard ^a,b  

^a University of Iowa   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

Lung segmentation; optimal surface finding; rib detection; robust active shape model

Indexed keywords

3D SEGMENTATION; ACTIVE SHAPE MODELS; AUTOMATED APPROACH; CT DATA; DATA SETS; DETECTION METHODS; DICE COEFFICIENT; HIGH-DENSITY; INITIAL POSITION; INITIAL SEGMENTATION; LUNG CANCER; LUNG SEGMENTATION; MATCHING METHODS; OPTIMAL SURFACE FINDING; PROCESSING STEPS; SEGMENTATION RESULTS; SHAPE MODEL;

BIOLOGICAL ORGANS; DISEASES; IMAGE SEGMENTATION; OPTIMIZATION;

THREE DIMENSIONAL;

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

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

EID: 84856751385     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2011.2171357     Document Type: Article

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