Noise Reduction for SD-OCT Using a Structure-Preserving Domain Transfer Approach
Spectral-domain optical coherence tomography (SD-OCT) images inevitably suffer from multiplicative speckle noise caused by random interference. This study proposes an unsupervised domain adaptation approach for noise reduction by translating the SD-OCT to the corresponding high-quality enhanced depth imaging (EDI)-OCT. We propose a structure-persevered cycle-consistent generative adversarial network for unpaired image-to-image translation, which can be applied to imbalanced unpaired data, and can effectively preserve retinal details based on a structure-specific cross-domain description. It also imposes smoothness by penalizing the intensity variation of the low reflective region between consecutive slices. Our approach was tested on a local data set that consisted ...
Login to comment.