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Open Access Gold as soon as Publ. Version/Full Text is submitted to ZB.
Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements.
Biomed. Opt. Express 4, 1104-1118 (2013)
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Independent Component Analysis ; Tomography ; Algorithms
ISSN (print) / ISBN
2156-7085
e-ISSN
2156-7085
Journal
Biomedical Optics Express
Quellenangaben
Volume: 4,
Issue: 7,
Pages: 1104-1118
Publisher
Optical Society of America (OSA)
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Biological and Medical Imaging (IBMI)