Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, USA.
School of Continuing and Lifelong Education, National University of Singapore, Singapore.
Comput Biol Med. 2023 Mar;155:106658. doi: 10.1016/j.compbiomed.2023.106658. Epub 2023 Feb 13.
A multiscale extension for the well-known block matching and 4D filtering (BM4D) method is proposed by analyzing and extending the wavelet subbands denoising method in such a way that the proposed method avoids directly denoising detail subbands, which considerably simplifies the computations and makes the multiscale processing feasible in 3D. To this end, we first derive the multiscale construction method in 2D and propose multiscale extensions for three 2D natural image denoising methods. Then, the derivation is extended to 3D by proposing mixed multiscale BM4D (mmBM4D) for optical coherence tomography (OCT) image denoising. We tested mmBM4D on three public OCT datasets captured by various imaging devices. The experiments revealed that mmBM4D significantly outperforms its original counterpart and performs on par with the state-of-the-art OCT denoising methods. In terms of peak-signal-to-noise-ratio (PSNR), mmBM4D surpasses the original BM4D by more than 0.68 decibels over the first dataset. In the second and third datasets, significant improvements in the mean to standard deviation ratio, contrast to noise ratio, and equivalent number of looks were achieved. Furthermore, on the downstream task of retinal layer segmentation, the layer quality preservation of the compared OCT denoising methods is evaluated.
提出了一种多尺度扩展的知名块匹配和 4D 滤波 (BM4D) 方法,通过分析和扩展小波子带去噪方法,使得该方法避免了直接对细节子带进行去噪,从而大大简化了计算,使 3D 中的多尺度处理成为可能。为此,我们首先在 2D 中推导出多尺度构建方法,并为三种 2D 自然图像去噪方法提出了多尺度扩展。然后,通过提出用于光学相干断层扫描 (OCT) 图像去噪的混合多尺度 BM4D (mmBM4D),将推导扩展到 3D。我们在三个由不同成像设备捕获的公共 OCT 数据集上测试了 mmBM4D。实验表明,mmBM4D 显著优于其原始方法,并与最先进的 OCT 去噪方法相当。在峰值信噪比 (PSNR) 方面,mmBM4D 在第一个数据集上超过原始 BM4D 超过 0.68 分贝。在第二和第三个数据集上,实现了平均到标准差比、对比噪声比和等效视数的显著提高。此外,在下游的视网膜层分割任务中,评估了比较的 OCT 去噪方法的层质量保持情况。