Learning active shape models for bifurcating contours

IEEE Transactions on Medical Imaging

Volumn 26, Issue 5, 2007, Pages 666-677

  Seise, Matthias ^b   McKenna, Stephen J ^a,b   Ricketts, Ian W ^a,b   Wigderowitz, Carlos A ^b  

^a IEEE   (United Kingdom)

^b UNIVERSITY OF DUNDEE   (United Kingdom)

Author keywords

Active shape models; Image segmentation; Image shape analysis; Osteoarthritis; X ray imaging

Indexed keywords

ACTIVE SHAPE MODELS; IMAGE SHAPE ANALYSIS; OSTEOARTHRITIS; X-RAY IMAGING;

BIFURCATION (MATHEMATICS); DIAGNOSIS; IMAGE SEGMENTATION; MEDICAL IMAGING; MEDICAL PROBLEMS; X RAY RADIOGRAPHY;

LEARNING SYSTEMS;

ALGORITHM; ARTHROGRAPHY; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE QUALITY; KNEE; KNEE OSTEOARTHRITIS; LIP; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTHROGRAPHY; ARTIFICIAL INTELLIGENCE; HUMANS; KNEE JOINT; LIP; OSTEOARTHRITIS, KNEE; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34247554484     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2007.895479     Document Type: Article

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