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- W4382246283 abstract "Optical Coherence Tomography (OCT) has become an important auxiliary diagnostic technology in the field of fundus disease detection due to its advantages of high resolution and high penetration depth. However, speckle noise exists in retinal images acquired by OCT. It is a difficult problem for OCT image processing technology to keep the middle layer structure information in the process of OCT image denoising. A novel OCT retinal image denoising method based on Gaussian mixture model and variational image decomposition is proposed. Firstly, the proposed BL-G-BM3D variational image decomposition model is used to initially denoise OCT images, and then the Gaussian mixture model is used to cluster the initial denoising results to obtain binary masks that can distinguish background and structure. Finally, the final denoising results are obtained by multiplying the mask image with the initial denoising results. An OCT retinal image with high noise and low contrast was tested and compared with five commonly used denoising methods. The results show that the proposed method can achieve both de-noising effect and laminar structure preservation for high-noise OCT retinal images." @default.
- W4382246283 created "2023-06-28" @default.
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- W4382246283 date "2023-06-27" @default.
- W4382246283 modified "2023-09-25" @default.
- W4382246283 title "An improved OCT retinal image denoising algorithm based on variational image decomposition" @default.
- W4382246283 doi "https://doi.org/10.1117/12.2680202" @default.
- W4382246283 hasPublicationYear "2023" @default.
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