Detecting and classifying linear structures in mammograms using random forests

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6801 LNCS, Issue , 2011, Pages 510-524

  Berks, Michael ^a   Chen, Zezhi ^a   Astley, Sue ^a   Taylor, Chris ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

classification; dual tree complex wavelet; linear structure detection; mammography; random forests; regression; spiculated lesions

Indexed keywords

DUAL-TREE COMPLEX WAVELETS; LINEAR STRUCTURE DETECTION; RANDOM FORESTS; REGRESSION; SPICULATED LESIONS;

DATA PROCESSING; DECISION TREES; MAMMOGRAPHY; PARTIAL DISCHARGES; X RAY SCREENS;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; FEMALE; HUMAN; IMAGE QUALITY; MAMMOGRAPHY; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BREAST NEOPLASMS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; LINEAR MODELS; MAMMOGRAPHY; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 80052318695     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22092-0_42     Document Type: Conference Paper

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