• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising.混合多尺度 BM4D 用于三维光学相干层析成像去噪。
Comput Biol Med. 2023 Mar;155:106658. doi: 10.1016/j.compbiomed.2023.106658. Epub 2023 Feb 13.
2
Multi-task generative adversarial network for retinal optical coherence tomography image denoising.用于视网膜光学相干断层扫描图像去噪的多任务生成对抗网络。
Phys Med Biol. 2023 Feb 3;68(4). doi: 10.1088/1361-6560/ac944a.
3
Noise-imitation learning: unpaired speckle noise reduction for optical coherence tomography.噪声模拟学习:用于光学相干断层扫描的非配对散斑噪声减少。
Phys Med Biol. 2024 Sep 3;69(18). doi: 10.1088/1361-6560/ad708c.
4
Optical coherence tomography retinal image reconstruction via nonlocal weighted sparse representation.基于非局部加权稀疏表示的光学相干断层扫描视网膜图像重建。
J Biomed Opt. 2018 Mar;23(3):1-11. doi: 10.1117/1.JBO.23.3.036011.
5
New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images.用于同时去噪和分割光学相干断层扫描图像的新型变分图像分解模型。
Phys Med Biol. 2015 Nov 21;60(22):8901-22. doi: 10.1088/0031-9155/60/22/8901. Epub 2015 Nov 10.
6
High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).利用协同波控随机混叠并行成像和混合降噪生成对抗网络(HDnGAN)进行高保真快速容积式脑部 MRI。
Med Phys. 2022 Feb;49(2):1000-1014. doi: 10.1002/mp.15427. Epub 2022 Jan 10.
7
Speckle reduction in optical coherence tomography images based on wave atoms.基于波原子的光学相干断层扫描图像散斑减少。
J Biomed Opt. 2014 May;19(5):056009. doi: 10.1117/1.JBO.19.5.056009.
8
Adaptive compounding speckle-noise-reduction filter for optical coherence tomography images.自适应复合散斑噪声降低滤波器用于光学相干断层扫描图像。
J Biomed Opt. 2021 Jun;26(6). doi: 10.1117/1.JBO.26.6.065001.
9
X-Let's Atom Combinations for Modeling and Denoising of OCT Images by Modified Morphological Component Analysis.X-基于改进形态成分分析的 OCT 图像建模和去噪的原子组合。
IEEE Trans Med Imaging. 2024 Feb;43(2):760-770. doi: 10.1109/TMI.2023.3320977. Epub 2024 Feb 2.
10
DHNet: High-resolution and hierarchical network for cross-domain OCT speckle noise reduction.DHNet:用于跨域 OCT 散斑噪声降低的高分辨率和层次网络。
Med Phys. 2022 Sep;49(9):5914-5928. doi: 10.1002/mp.15712. Epub 2022 Jun 1.

引用本文的文献

1
Physics-guided deep learning-based real-time image reconstruction of Fourier-domain optical coherence tomography.基于物理引导深度学习的傅里叶域光学相干断层扫描实时图像重建
Biomed Opt Express. 2024 Oct 30;15(11):6619-6637. doi: 10.1364/BOE.538756. eCollection 2024 Nov 1.

本文引用的文献

1
Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images.Livelayer:一种用于光学相干断层扫描图像中分层和糖尿病性黄斑水肿自动分割的半自动软件程序。
Sci Rep. 2021 Jul 2;11(1):13794. doi: 10.1038/s41598-021-92713-y.
2
OCT-GAN: single step shadow and noise removal from optical coherence tomography images of the human optic nerve head.OCT-GAN:从人视神经乳头的光学相干断层扫描图像中一步去除阴影和噪声
Biomed Opt Express. 2021 Feb 19;12(3):1482-1498. doi: 10.1364/BOE.412156. eCollection 2021 Mar 1.
3
Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images.基于噪声的解缠表示在光学相干断层扫描图像无监督散斑降噪中的应用。
IEEE Trans Med Imaging. 2021 Oct;40(10):2600-2614. doi: 10.1109/TMI.2020.3045207. Epub 2021 Sep 30.
4
Reconstruction of Optical Coherence Tomography Images Using Mixed Low Rank Approximation and Second Order Tensor Based Total Variation Method.基于混合低秩逼近和二阶张量总变分的光学相干断层扫描图像重建。
IEEE Trans Med Imaging. 2021 Mar;40(3):865-878. doi: 10.1109/TMI.2020.3040270. Epub 2021 Mar 2.
5
N2NSR-OCT: Simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning.N2NSR-OCT:使用半监督深度学习在光学相干断层扫描图像中同时进行去噪和超分辨率处理
J Biophotonics. 2021 Jan;14(1):e202000282. doi: 10.1002/jbio.202000282. Epub 2020 Oct 19.
6
Multivariate Statistical Modeling of Retinal Optical Coherence Tomography.视网膜光学相干断层扫描的多元统计建模。
IEEE Trans Med Imaging. 2020 Nov;39(11):3475-3487. doi: 10.1109/TMI.2020.2998066. Epub 2020 Oct 28.
7
Automatically Enhanced OCT Scans of the Retina: A proof of concept study.自动增强的视网膜 OCT 扫描:概念验证研究。
Sci Rep. 2020 May 8;10(1):7819. doi: 10.1038/s41598-020-64724-8.
8
Super-Resolution of Optical Coherence Tomography Images by Scale Mixture Models.基于尺度混合模型的光学相干断层扫描图像超分辨率技术
IEEE Trans Image Process. 2020 Apr 7. doi: 10.1109/TIP.2020.2984896.
9
Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function.使用具有感知敏感损失函数的深度神经网络降低光学相干断层扫描图像中的噪声
Biomed Opt Express. 2020 Jan 14;11(2):817-830. doi: 10.1364/BOE.379551. eCollection 2020 Feb 1.
10
Three-dimensional curvelet-based dictionary learning for speckle noise removal of optical coherence tomography.基于三维曲波的字典学习用于光学相干断层扫描散斑噪声去除
Biomed Opt Express. 2020 Jan 3;11(2):586-608. doi: 10.1364/BOE.377021. eCollection 2020 Feb 1.

混合多尺度 BM4D 用于三维光学相干层析成像去噪。

Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising.

机构信息

Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, USA.

School of Continuing and Lifelong Education, National University of Singapore, Singapore.

出版信息

Comput Biol Med. 2023 Mar;155:106658. doi: 10.1016/j.compbiomed.2023.106658. Epub 2023 Feb 13.

DOI:10.1016/j.compbiomed.2023.106658
PMID:36827787
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10739784/
Abstract

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.

摘要

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。