Optical coherence tomography is a three-dimensional imaging modality that captures microstructures of the tissue. The application of OCT in dermatology is limited due to the low visibility in these images. Numerous image denoising and enhancement algorithms have been implemented for quality improvement of the OCT skin images. One way to evaluate the performance of these algorithms is to quantify the quality of the processed images using different image quality metrices. Current image quality metrics though do not fairly represent the visual quality of the images. We propose an algorithm to quantify the quality of OCT images compatible with human visual perception, and the diagnostically important features in skin images. We implement a new metric called Signal to Noise Ratio. The metric is assessed on different number of averaged OCT images taken from the same cross section of the skin.
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