Interactive lesion segmentation with shape priors from offline and online learning

IEEE Transactions on Medical Imaging

Volumn 31, Issue 9, 2012, Pages 1698-1712

  Shepherd, Tony ^a   Prince, Simon J D ^b   Alexander, Daniel C ^b  

^a TURKU UNIVERSITY HOSPITAL   (Finland)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Active shapemodel; Biomedical image processing; Image segmentation; Machine learning; Stochastic processes

Indexed keywords

ACTIVE SHAPEMODEL; AUTOMATIC SEGMENTATIONS; BIO-MEDICAL IMAGE PROCESSING; BOUNDARY FLUCTUATIONS; DYNAMIC CONTOUR MODELS; INTERACTIVE ALGORITHMS; MACHINE LEARNING TECHNIQUES; MEDICAL IMAGE SEGMENTATION; NONLINEAR TIME SERIES; OFFLINE; ONE-FACTOR; ONLINE LEARNING; SENSITIVITY AND SPECIFICITY; SHAPE INFORMATION; SHAPE MODELLING; SHAPE PARAMETERIZATION; SHAPE PRIORS; STATISTICAL SHAPE MODEL; TRAINING DATA; USER DEMANDS; USER INTERACTION;

IMAGE PROCESSING; IMAGE SEGMENTATION; LEARNING SYSTEMS; MEDICAL IMAGE PROCESSING; RANDOM PROCESSES; TUMORS;

E-LEARNING;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE PROCESSING; LIVER TUMOR; METHODOLOGY; MULTIPLE SCLEROSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; STATISTICS;

ALGORITHMS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LIVER NEOPLASMS; MAGNETIC RESONANCE IMAGING; MULTIPLE SCLEROSIS; ROC CURVE; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84867494287     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2012.2196285     Document Type: Article

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