A generic probabilistic active shape model for organ segmentation

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 26-33

  Wimmer, Andreas ^a,b   Soza, Grzegorz ^b   Hornegger, Joachim ^a  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE SHAPE MODELS; AUTOMATIC METHOD; AVERAGE VOLUME; BOOSTED CLASSIFIERS; BOUNDARY APPEARANCE; DENSITY ESTIMATES; LIVER SEGMENTATION; MEDICAL IMAGE SEGMENTATION; NEAREST NEIGHBORS; NON-PARAMETRIC; ORGAN SEGMENTATION; PARAMETRIC REPRESENTATIONS; PARZEN DENSITY ESTIMATION; PROBABILISTIC MODELS; PUBLIC DATA; REGION INFORMATION; SHAPE MODEL; SINGLE LEVEL;

FACE RECOGNITION; LIVER; MEDICAL COMPUTING; NORMAL DISTRIBUTION; SPEECH RECOGNITION;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUDIOVISUAL EQUIPMENT; 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;

ALGORITHMS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; LIVER; MODELS, ANATOMIC; 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: 80052048343     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_4     Document Type: Conference Paper

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