Research Papers: Imaging

Automated classification of breast pathology using local measures of broadband reflectance

[+] Author Affiliations
Ashley M. Laughney, Venkataramanan Krishnaswamy

Dartmouth College, Thayer School of Engineering, 8000 Cummings Hall, Hanover, New Hampshire 03755

Pilar Beatriz Garcia-Allende

University of Cantabria, Photonics Engineering Group, Avda. de los Castros S/N, Santander 39005, Spain and Imperial College London, Department of Surgery and Cancer, Exhibition Road, London SW7 2AZ, United Kingdom

Olga M. Conde

University of Cantabria, Photonics Engineering Group, Avda. de los Castros S/N, Santander 39005, Spain

Wendy A. Wells

Dartmouth-Hitchcock Medical Center, Department of Pathology, 1 Medical Center Drive, Lebanon, New Hampshire 03756

Keith D. Paulsen, Brian W. Pogue

Dartmouth College, Thayer School of Engineering, 8000 Cummings Hall, Hanover, New Hampshire 03755

J. Biomed. Opt. 15(6), 066019 (December 30, 2010). doi:10.1117/1.3516594
History: Received May 02, 2010; Revised September 26, 2010; Accepted October 04, 2010; Published December 30, 2010; Online December 30, 2010
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We demonstrate that morphological features pertinent to a tissue's pathology may be ascertained from localized measures of broadband reflectance, with a mesoscopic resolution (100-μm lateral spot size) that permits scanning of an entire margin for residual disease. The technical aspects and optimization of a k-nearest neighbor classifier for automated diagnosis of pathologies are presented, and its efficacy is validated in 29 breast tissue specimens. When discriminating between benign and malignant pathologies, a sensitivity and specificity of 91 and 77% was achieved. Furthermore, detailed subtissue-type analysis was performed to consider how diverse pathologies influence scattering response and overall classification efficacy. The increased sensitivity of this technique may render it useful to guide the surgeon or pathologist where to sample pathology for microscopic assessment.

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© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Ashley M. Laughney ; Venkataramanan Krishnaswamy ; Pilar Beatriz Garcia-Allende ; Olga M. Conde ; Wendy A. Wells, et al.
"Automated classification of breast pathology using local measures of broadband reflectance", J. Biomed. Opt. 15(6), 066019 (December 30, 2010). ; http://dx.doi.org/10.1117/1.3516594


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