Prostate-cancer imaging using machine-learning classifiers: Potential value for guiding biopsies, targeting therapy, and monitoring treatment

Proceedings - IEEE Ultrasonics Symposium

Volumn , Issue , 2009, Pages 527-529

  Feleppa, Ernest J ^a   Rondeau, Mark J ^a   Lee, Paul ^a   Porter, Christopher R ^b  

^a RIVERSIDE RESEARCH INSTITUTE   (United States)

^b VIRGINIA MASON MEDICAL CENTER   (United States)

Author keywords

Non linear classifiers; Prostate cancer; Quantitative ultrasound; Spectrum analysis; Tissue type images

Indexed keywords

BIOPSY; CALCIUM COMPOUNDS; DISEASES; IMAGE SEGMENTATION; MACHINE LEARNING; MEDICAL IMAGING; MULTILAYER NEURAL NETWORKS; SPECTRUM ANALYSIS; SUPPORT VECTOR MACHINES; ULTRASONIC IMAGING; UROLOGY;

CROSS-VALIDATION METHODS; NONLINEAR CLASSIFIERS; PROSTATE CANCERS; PROSTATE-CANCER IMAGING; QUANTITATIVE ULTRASOUNDS; RESTRICTED BOLTZMANN MACHINE; SUPPORT VECTOR MACHINE (SVMS); TISSUE-TYPE IMAGES;

TISSUE;

EID: 77952840242     PISSN: 10510117     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ULTSYM.2009.5442061     Document Type: Conference Paper

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