In this study, we present a new algorithm based on an artificial neural network (ANN) for reducing speckle noise from optical coherence tomography (OCT) images. The noise is modeled for different parts of the image using Rayleigh distribution with a noise parameter, sigma, estimated by the ANN. This is then used along with a numerical method to solve the inverse Rayleigh function to reduce the noise in the image. The algorithm is tested successfully on OCT images of retina, demonstrating a significant increase in the signal-to-noise ratio (SNR) and the contrast of the processed images.

Date Published: 4 March 2014
PDF: 9 pages
Proc. SPIE 8934, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVIII, 893437 (4 March 2014); doi: 10.1117/12.2041943

Published in SPIE Proceedings Vol. 8934:
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVIII
Joseph A. Izatt; James G. Fujimoto; Valery V. Tuchin, Editor(s)