Quantitative Analysis of Lesion Morphology and Texture Features for Diagnostic Prediction in Breast MRI

Academic Radiology

Volumn 15, Issue 12, 2008, Pages 1513-1525

  Nie, Ke ^a   Chen, Jeon Hor ^a,b   Yu, Hon J ^a   Chu, Yong ^a   Nalcioglu, Orhan ^a   Su, Min Ying ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b CHINA MEDICAL UNIVERSITY HOSPITAL   (Taiwan)

Author keywords

Artificial neural network; BI RADS; breast MRI; computer aided diagnosis; lesion characterization

Indexed keywords

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST LESION; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; INTERMETHOD COMPARISON; MORPHOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PHENOTYPE; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; RECEIVER OPERATING CHARACTERISTIC;

ADULT; AGED; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; FEASIBILITY STUDIES; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 55349148361     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2008.06.005     Document Type: Article

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