A novel approach for global lung registration using 3D Markov-Gibbs appearance model

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

Volumn 7511 LNCS, Issue , 2012, Pages 114-121

  El Baz, Ayman ^a   Khalifa, Fahmi ^a   Elnakib, Ahmed ^a   Nitzken, Matthew ^a   Soliman, Ahmed ^a   McClure, Patrick ^a   Abou El Ghar, Mohamed ^b   Gimel’Farb, Georgy ^c  

^a University of Louisville   (United States)

^b MANSOURA UNIVERSITY   (Egypt)

^c UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ORGANS; MEDICAL COMPUTING; MEDICAL IMAGING; METADATA;

3D MARKOV-GIBBS RANDOM FIELDS; AFFINE TRANSFORMATIONS; APPEARANCE MODELING; AUTOMATIC INITIALIZATION; CONVENTIONAL ALGORITHMS; GRADIENT SEARCH; PAIRWISE INTERACTION; VISUAL APPEARANCE;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE QUALITY; IMAGE SUBTRACTION; LUNG; METHODOLOGY; PROBABILITY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THORAX RADIOGRAPHY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; IMAGING, THREE-DIMENSIONAL; LUNG; MARKOV CHAINS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84872899934     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33418-4_15     Document Type: Conference Paper

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