Novel stochastic framework for accurate segmentation of prostate in dynamic contrast enhanced MRI

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

Volumn 6367 LNCS, Issue , 2010, Pages 121-130

  Firjany, Ahmad ^a   Elnakib, Ahmed ^a   El Baz, Ayman ^a   Gimel'farb, Georgy ^b   El Ghar, Mohamed Abo ^c   Elmagharby, Adel ^a  

^a University of Louisville   (United States)

^b UNIVERSITY OF AUCKLAND   (New Zealand)

^c MANSOURA UNIVERSITY   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ASSISTED; DCE-MRI; DESCRIPTORS; DYNAMIC CONTRAST ENHANCED MRI; DYNAMIC CONTRAST ENHANCEMENT; EARLY DIAGNOSIS; ENERGY FUNCTIONS; GRAPH CUT; GRAY LEVELS; MAGNETIC RESONANCE IMAGES; MARKOV-GIBBS RANDOM FIELDS; MR IMAGES; NON-INVASIVE; PROSTATE CANCERS; PROSTATE SEGMENTATION; ROTATION INVARIANT; SHAPE DESCRIPTORS; SHAPE PRIORS; SPATIAL INTERACTION; STOCHASTIC FRAMEWORK; TRAINING IMAGE; VISUAL APPEARANCE;

DISEASES; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; VISUALIZATION;

COMPUTER AIDED DIAGNOSIS;

EID: 78149387975     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15989-3_14     Document Type: Conference Paper

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