Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk

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

Volumn 8150 LNCS, Issue PART 2, 2013, Pages 295-302

  Mahrooghy, Majid ^a   Ashraf, Ahmed B ^a   Daye, Danya ^a   Mies, Carolyn ^a   Feldman, Michael ^a   Rosen, Mark ^a   Kontos, Despina ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

breast cancer recurrence prediction; Breast DCE MRI; breast tumor heterogeneity partitioning; tumor feature extraction

Indexed keywords

BREAST CANCER; BREAST DCE MRIS; BREAST TUMOR; DYNAMIC CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING; LOGISTIC REGRESSION CLASSIFIER; SPATIOTEMPORAL PATTERNS; TUMOR CHARACTERIZATION; WAVELET COEFFICIENTS;

DISEASES; FEATURE EXTRACTION; GENE EXPRESSION; KINETICS; MAGNETIC RESONANCE IMAGING; TUMORS;

DIAGNOSIS;

ADULT; AGED; ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; FEMALE; HUMAN; METHODOLOGY; MIDDLE AGED; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; RISK FACTOR; SENSITIVITY AND SPECIFICITY; TUMOR RECURRENCE; WAVELET ANALYSIS;

ADULT; AGED; ALGORITHMS; BREAST NEOPLASMS; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MIDDLE AGED; MODELS, GENETIC; NEOPLASM RECURRENCE, LOCAL; REPRODUCIBILITY OF RESULTS; RISK FACTORS; SENSITIVITY AND SPECIFICITY; WAVELET ANALYSIS;

EID: 84885937984     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40763-5_37     Document Type: Conference Paper

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