Document Type
Article
Publication Date
7-1-2013
Publication Title
Biomedical Optics Express
Department
Thayer School of Engineering
Abstract
Breast tumors are blindly identified using Principal (PCA) and Independent Component Analysis (ICA) of localized reflectance measurements. No assumption of a pa rticular theoretical model for the reflectance needs to be made, while the re sulting features are proven to have discriminative power of breast pathologies. Normal, benign and malignant breast tissue types in lumpect omy 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.
DOI
10.1364/BOE.4.001104
Original Citation
Eguizabal A, Laughney AM, García-Allende PB, Krishnaswamy V, Wells WA, Paulsen KD, Pogue BW, Lopez-Higuera JM, Conde OM. Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements. Biomed Opt Express. 2013 Jun 12;4(7):1104-18. doi: 10.1364/BOE.4.001104. PMID: 23847736; PMCID: PMC3704092.
Dartmouth Digital Commons Citation
Eguizabal, Alma; Laughney, Ashley M.; García-Allende, Pilar Beatriz; Krishnaswamy, Venkataramanan; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.; Lopez-Higuera, Jose M.; and Conde, Olga M., "Direct Identification of Breast Cancer Pathologies Using Blind Separation of Label-Free Localized Reflectance Measurements" (2013). Dartmouth Scholarship. 2637.
https://digitalcommons.dartmouth.edu/facoa/2637
