Liver segmentation using automatically defined patient specific B-spline surface models

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

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 43-50

  Song, Yi ^a   Bulpitt, Andy J ^a   Brodlie, Ken W ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

B-SPLINE SURFACE MODELS; COMPLEX SHAPES; COMPUTATION EFFICIENCY; CT IMAGE; LIVER REGIONS; LIVER SEGMENTATION; MANUAL SEGMENTATION; MODEL DRIVEN APPROACH; NARROW BANDS; NON-TRIVIAL; PATIENT SPECIFIC; PRE-SEGMENTATION; PROCESSING TIME; RMS ERRORS; ROBUST GRAPHS; STATISTICAL MODELS; SUB-REGIONS; SURFACE FITTING; TRAINING REQUIREMENT; TRAINING SETS;

IMAGE SEGMENTATION; LIVER; MEDICAL COMPUTING; SPLINES;

COMPUTERIZED TOMOGRAPHY;

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

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

EID: 80055099853     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_6     Document Type: Conference Paper

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