A Computer-Aided Diagnostic System to Characterize CT Focal Liver Lesions: Design and Optimization of a Neural Network Classifier

IEEE Transactions on Information Technology in Biomedicine

Volumn 7, Issue 3, 2003, Pages 153-162

  Gletsos, Miltiades ^a   Mougiakakou, Stavroula G ^a   Matsopoulos, George K ^a   Nikita, Konstantina S ^a   Nikita, Alexandra S ^b   Kelekis, Dimitrios ^b  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^b UNIVERSITY OF ATHENS MEDICAL SCHOOL   (Greece)

Author keywords

Feature selection; Liver CT; Neural networks; Texture features

Indexed keywords

BIOPSY; COMPUTER AIDED DESIGN; DECISION SUPPORT SYSTEMS; FEATURE EXTRACTION; GASTROENTEROLOGY; GENETIC ALGORITHMS; MAMMOGRAPHY; MEDICAL IMAGING; NEURAL NETWORKS; OPTIMIZATION; PATHOLOGY; STATISTICAL METHODS; TUMORS;

FEATURE SELECTION; LIVER COMPUTED TOMOGRAPHY (CT); TEXTURE FEATURES;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CLINICAL TRIAL; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; CYST; HEMANGIOMA; HUMAN; IMAGE QUALITY; LIVER; LIVER CELL CARCINOMA; LIVER TUMOR; METHODOLOGY; PATHOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY;

ALGORITHMS; CARCINOMA, HEPATOCELLULAR; CYSTS; HEMANGIOMA; HUMANS; LIVER; LIVER NEOPLASMS; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 0142182181     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2003.813793     Document Type: Article

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