Studies on quantitative analysis and automatic recognition of cell types of lung cancer

Bio-Medical Materials and Engineering

Volumn 16, Issue 2, 2006, Pages 119-128

  Chen, Yi Chen ^a   Hu, Kuang Hu ^a   Li, Fang Zhen ^a   Li, Shu Yu ^a   Su, Wan Fang ^a   Huang, Zhi Ying ^b   Hu, Ying Xiong ^c  

^a INSTITUTE OF BIOPHYSICS   (China)

^b Beijing Institute of Pulmonary Tuberculosis and Tumors   (China)

^c China Natl Software/Technol Co   (China)

Author keywords

Classification and recognition; Clinical assistant diagnoses; Lung cancer cells; Mathematical morphology

Indexed keywords

BIOLOGICAL ORGANS; CELL CULTURE; DIAGNOSIS; IMAGE ANALYSIS; MATHEMATICAL TECHNIQUES; PARAMETER ESTIMATION;

CLASSIFICATION AND RECOGNITION; CLINICAL ASSISTANT DIAGNOSES; LUNG CANCER CELLS; SUBORDINATE IMAGES;

ONCOLOGY;

ADULT; AGED; ANALYTICAL PARAMETERS; ARTICLE; AUTOANALYSIS; CANCER CELL; CANCER DIAGNOSIS; CELL SHAPE; CELL STRUCTURE; CELL TYPE; CLINICAL TRIAL; COMPUTER PROGRAM; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIAGNOSTIC VALUE; FEMALE; HUMAN; HUMAN CELL; IMAGE ANALYSIS; IMAGE QUALITY; LUNG CANCER; MAJOR CLINICAL STUDY; MALE; MATHEMATICS; METHODOLOGY; NOISE; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS;

ADULT; AGED; ALGORITHMS; ARTIFICIAL INTELLIGENCE; CARCINOMA; CLUSTER ANALYSIS; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LUNG NEOPLASMS; MALE; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 32344438312     PISSN: 09592989     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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