Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and t -SNE

Medical Physics

Volumn 37, Issue 1, 2010, Pages 339-351

  Jamieson, Andrew R ^a   Giger, Maryellen L ^a   Drukker, Karen ^a   Li, Hui ^a   Yuan, Yading ^a   Bhooshan, Neha ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Breast cancer; Computer aided diagnosis; Laplacian eigenmaps; Nonlinear dimension reduction; T SNE

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DIMENSIONALITY REDUCTION; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; LAPLACE TRANSFORMS; MAGNETIC RESONANCE IMAGING; MAMMOGRAPHY; MAPPING; MARKOV CHAINS; MEDICAL IMAGING; NONLINEAR ANALYSIS; STOCHASTIC SYSTEMS; ULTRASONIC APPLICATIONS;

AUTOMATIC RELEVANCE DETERMINATION; BAYESIAN ARTIFICIAL NEURAL NETWORKS; BREAST CANCER; DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE IMAGING; HIGH-DIMENSIONAL FEATURE SPACE; LAPLACIAN EIGENMAPS; NONLINEAR DIMENSION; T-SNE;

DATA REDUCTION;

EID: 73649088617     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3267037     Document Type: Article

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