ArticleBiomedical optics express2025
Time-step encoded high-frequency enhanced diffusion model for OCT retinal image denoising.
Article in Biomedical optics express, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Optical coherence tomography (OCT) is a widely used imaging technique in ophthalmology, capable of non-invasive, high-resolution imaging of retinal tissues. However, OCT images are often degraded by speckle noise, resulting in poor image quality. Deep learning-based denoising models have become the mainstream approach, but existing methods tend to oversmooth images and lose high-frequency details, making it difficult to recover the true retinal structure. This paper proposes a high-frequency enhanced diffusion model based on the cold diffusion framework, named THFN-OCT (time-enhanced high-frequency network for OCT denoising). The model decouples frequency-domain information and processes it separately, with cross-domain connections to preserve high-frequency details while ensuring denoising performance. In addition, considering the different impacts of each diffusion timestep on frequency components, we design a timestep-aware attention module that uses the timestep
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