Design of a multi-classifier system for discriminating benign from malignant thyroid nodules using routinely H&E-stained cytological images

Computers in Biology and Medicine

Volumn 38, Issue 2, 2008, Pages 196-203

  Daskalakis, Antonis ^a   Kostopoulos, Spiros ^a   Spyridonos, Panagiota ^a   Glotsos, Dimitris ^a   Ravazoula, Panagiota ^b   Kardari, Maria ^b   Kalatzis, Ioannis ^c   Cavouras, Dionisis ^c   Nikiforidis, George ^a  

^a UNIVERSITY OF PATRAS   (Greece)

^b UNIVERSITY HOSPITAL OF PATRAS   (Greece)

^c UNIVERSITY OF WEST ATTICA   (Greece)

Author keywords

Computer assisted microscopy; Cytological images; Hematoxylin Eosin; Multi classifier systems; Quantitative analysis of cell nuclei; Thyroid nodules

Indexed keywords

BAYESIAN NETWORKS; BIOMEDICAL EQUIPMENT; CHEMICAL ANALYSIS; CYTOLOGY; MEDICAL IMAGING;

CYTOLOGICAL IMAGES; HEMATOXYLIN; MULTI CLASSIFIER SYSTEMS; QUANTITATIVE ANALYSIS OF CELL NUCLEI; THYROID NODULES;

DIAGNOSIS;

EOSIN; HEMATOXYLIN;

ARTICLE; ASPIRATION BIOPSY; BAYES THEOREM; BENIGN TUMOR; CELL NUCLEUS; CELL STRUCTURE; CLASSIFIER; DIAGNOSTIC ACCURACY; DIAGNOSTIC PROCEDURE; DISEASE CLASSIFICATION; HUMAN; HUMAN TISSUE; MALIGNANT NEOPLASTIC DISEASE; PRIORITY JOURNAL; STAINING; THYROID NODULE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BIOPSY, FINE-NEEDLE; CELL NUCLEUS; CYTODIAGNOSIS; DIAGNOSIS, DIFFERENTIAL; EOSINE YELLOWISH-(YS); HEMATOXYLIN; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LEAST-SQUARES ANALYSIS; NEURAL NETWORKS (COMPUTER); SENSITIVITY AND SPECIFICITY; STAINING AND LABELING; STATISTICS, NONPARAMETRIC; THYROID GLAND; THYROID NEOPLASMS; THYROID NODULE;

EID: 37549015967     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2007.09.005     Document Type: Article

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