Texture guided active appearance model propagation for prostate segmentation

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

Volumn 6367 LNCS, Issue , 2010, Pages 111-120

  Ghose, Soumya ^a,b   Oliver, Arnau ^a   Martí, Robert ^a   Lladó, Xavier ^a   Freixenet, Jordi ^a   Vilanova, Joan C ^c   Meriaudeau, Fabrice ^b  

^a UNIVERSITY OF GIRONA   (Spain)

^b UNIVERSITÉ DE BOURGOGNE   (France)

^c Girona Magnetic Resonance Center   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE APPEARANCE MODELS; APPEARANCE BASED; APPROXIMATION COEFFICIENTS; COMPUTATIONAL COSTS; COMPUTATIONALLY EFFICIENT; HAAR WAVELET TRANSFORM; IMAGING ARTIFACTS; INTENSITY DISTRIBUTION; INTENSITY HETEROGENEITY; LEAVE-ONE-OUT; LOW SIGNAL-TO-NOISE RATIO; MALIGNANT TISSUES; MULTI-RESOLUTIONS; PARAMETRIC MODELS; PRIOR KNOWLEDGE; PROSTATE BIOPSY; PROSTATE SEGMENTATION; REGISTRATION ACCURACY; SIMILARITY COEFFICIENTS; SPECKLE NOISE; STATISTICAL MODELS; TEXTURE FEATURES; TEXTURE INFORMATION; TRAINING DATA; TRUS IMAGES; VIDEO SEQUENCES;

DISEASES; FACE RECOGNITION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; OPTIMIZATION; PRINCIPAL COMPONENT ANALYSIS; RESONANCE; SIGNAL TO NOISE RATIO; TEXTURES; VIDEO RECORDING; WAVELET TRANSFORMS;

COMPUTER AIDED DIAGNOSIS;

EID: 78149386022     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15989-3_13     Document Type: Conference Paper

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