A Bayesian approach for liver analysis: Algorithm and validation study

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 85-92

  Freiman, Moti ^a   Eliassaf, Ofer ^a   Taieb, Yoav ^a   Joskowicz, Leo ^a   Sosna, Jacob ^b  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

^b HADASSAH HEBREW UNIVERSITY MEDICAL CENTER   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOURS; AUTOMATIC SEGMENTATIONS; BAYESIAN APPROACHES; BAYESIAN CLASSIFICATION; DATA SETS; GROUND TRUTH; INTENSITY DISTRIBUTION FUNCTIONS; INTERNAL PARAMETERS; LIVER VOLUME; METASTATIC LESIONS; MULTI-CLASS; MULTI-RESOLUTIONS; NEIGHBORHOOD INFORMATION; SEED SELECTION; SEMI-AUTOMATIC SEGMENTATION; VALIDATION STUDY;

BAYESIAN NETWORKS; COMPUTER SCIENCE; DISTRIBUTION FUNCTIONS; LIVER; MEDICAL IMAGING;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; EVALUATION; HUMAN; IMAGE QUALITY; LIVER; LIVER TUMOR; METHODOLOGY; RADIOGRAPHY; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; HUMANS; LIVER; LIVER NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; TOMOGRAPHY, X-RAY COMPUTED;

EID: 58849132470     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_11     Document Type: Conference Paper

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