Abstract
An automated, support-vector-machine classifier was developed to discriminate basal cell carcinoma from healthy mouse skin images obtained with polarization sensitive optical coherence tomography. The results demonstrate that polarization sensitive optical coherence tomography has the potential to achieve accurate diagnosis of skin cancer noninvasively.
© 2014 Optical Society of America
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