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Eguizabal, A.* ; Laughney, A.M.* ; Garcia-Allende, P. ; Krishnaswamy, V.* ; Wells, W.A.* ; Paulsen, K.D.* ; Pogue, B.W.* ; Lopez-Higuera, J.M.* ; Conde, O.M.*

Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements.

Biomed. Opt. Express 4, 1104-1118 (2013)
DOI
Open Access Gold möglich sobald Verlagsversion bei der ZB eingereicht worden ist.
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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Independent Component Analysis ; Tomography ; Algorithms
ISSN (print) / ISBN 2156-7085
e-ISSN 2156-7085
Quellenangaben Band: 4, Heft: 7, Seiten: 1104-1118 Artikelnummer: , Supplement: ,
Verlag Optical Society of America (OSA)
Begutachtungsstatus Peer reviewed