Automated Texture-based Quantification of Centrilobular Nodularity and Centrilobular Emphysema in Chest CT Images

Academic Radiology

Volumn 19, Issue 10, 2012, Pages 1241-1251

  Ginsburg, Shoshana B ^a   Lynch, David A ^b   Bowler, Russell P ^b   Schroeder, Joyce D ^b  

^a RUTGERS UNIVERSITY   (United States)

^b DEPARTMENT OF MEDICINE   (United States)

Author keywords

Centrilobular nodularity; Computer aided diagnosis; Emphysema; Texture analysis

Indexed keywords

ADULT; AGED; ARTICLE; AUTOMATED TEXTURE BASED SYSTEM; AUTOMATION; CENTRILOBULAR NODULARITY; CLINICAL ARTICLE; COHORT ANALYSIS; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; FEMALE; HUMAN; IMAGE ANALYSIS; LUNG EMPHYSEMA; LUNG PARENCHYMA; LYMPHADENOPATHY; MALE; PRIORITY JOURNAL; SMOKING; TRAINING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FEMALE; HUMANS; MALE; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; PULMONARY EMPHYSEMA; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84865767060     PISSN: 10766332     EISSN: 18784046     Source Type: Journal    
DOI: 10.1016/j.acra.2012.04.020     Document Type: Article

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