@article{10902/2586,
year = {2013},
month = {7},
url = {http://hdl.handle.net/10902/2586},
abstract = {Breast tumors are blindly identified using Principal (PCA) and Independent Component Analysis (ICA) of localized reflectance measurements. No assumption of a particular theoretical model for the reflectance needs to be made, while the resulting features are proven to have discriminative power of breast pathologies. Normal, benign and malignant breast tissue types in lumpectomy specimens were imaged ex vivo and a surgeon-guided calibration of the system is proposed to overcome the limitations of the blind analysis. A simple, fast and linear classifier has been proposed where no training information is required for the diagnosis. A set of 29 breast tissue specimens have been diagnosed with a sensitivity of 96% and specificity of 95% when discriminating benign from malignant pathologies. The proposed hybrid combination PCA-ICA enhanced diagnostic discrimination, providing tumor probability maps, and intermediate PCA parameters reflected tissue optical properties.},
organization = {This work has been supported by the Spanish Government through CYCIT projects DA2TOI (FIS2010-19860), TFS (TEC2010-20224-C02-02) and Alma’s Eguizabal PhD Grant (FPU12/04130) and by Dartmouth College.},
publisher = {The Optical Society (OSA)},
publisher = {Biomedical Optics Express, 2013, 4 (7), 1104-1118},
title = {Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements},
author = {Eguizabal Aguado, Alma and Laughney, Ashley M. and García Allende, Pilar Beatriz and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian William and López Higuera, José Miguel and Conde Portilla, Olga María},
}