Clustering-Oriented Multiple Convolutional Neural Networks for Optical Coherence Tomography Image Denoising

The speckle noise is an inherent coproduct of OCT imaging that is a significant direct influence factor of image quality, thus OCT image denoising is needed. Most existing OCT image denoising methods usually use only part of the priori information of the OCT image, but neglect the change of the texture, structure and other features of the OCT image. To address this, we introduce a framework for OCT image denoising by multiple CNNs based on clustering and residual learning. Our proposed method not only utilizes the automatic feature learning ability of CNNs but also adapts them to depict diversity of noise characteristics in different areas of noisy input. Our framework achieves great visual and quantitative performance.