Toward early diagnosis of lung cancer

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 682-689

  El Baz, Ayman ^a   Gimel'farb, Georgy ^b   Falk, Robert ^c   Abou El Ghar, Mohamed ^d   Rainey, Sabrina ^a   Heredia, David ^a   Shaffer, Teresa ^a  

^a University of Louisville   (United States)

^b UNIVERSITY OF AUCKLAND   (New Zealand)

^c JEWISH HOSPITAL   (United States)

^d MANSOURA UNIVERSITY   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE REGISTRATION; AFFINE TRANSFORMATIONS; APPEARANCE MODELS; CHEST IMAGE; COMPUTED TOMOGRAPHY; DATA REGISTRATION; DATA SETS; DIAGNOSTIC SYSTEMS; EARLY DIAGNOSIS; GIBBS ENERGY FUNCTIONS; GRADIENT ASCENT; IMAGE-BASED; ISO SURFACE; LOCAL ALIGNMENT; LOCAL DEFORMATIONS; LONG TERM; LOW DOSE; LUNG CANCER; LUNG NODULE; MARKOV-GIBBS RANDOM FIELDS; NON-RIGID; PAIRWISE INTERACTION; PROBABILISTIC MODELS; PULMONARY NODULES; RELATIVE DEFORMATION; RESEARCH GOALS; SPEED FUNCTION; VISUAL APPEARANCE;

ALIGNMENT; BIOLOGICAL ORGANS; COMPUTERIZED TOMOGRAPHY; DEFORMATION; MEDICAL COMPUTING; TARGETS; VISUALIZATION;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE QUALITY; LUNG TUMOR; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; HUMANS; IMAGING, THREE-DIMENSIONAL; LUNG NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 82955224214     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_83     Document Type: Conference Paper

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