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??博主優(yōu)勢(shì)：??????博客內(nèi)容盡量做到思維縝密，邏輯清晰，為了方便讀者。
??座右銘：行百里者，半于九十。
??????本文目錄如下：??????
目錄
??1 概述
??2 運(yùn)行結(jié)果
??3?參考文獻(xiàn)
??4 Matlab代碼、數(shù)據(jù)、文章
??1 概述
文獻(xiàn)來(lái)源：
?摘要：
高速相干拉曼散射成像通過(guò)可視化目標(biāo)分子或細(xì)胞內(nèi)細(xì)胞器的時(shí)空動(dòng)力學(xué)，為揭示細(xì)胞機(jī)制開(kāi)辟了一條新途徑。通過(guò)以MHz調(diào)制頻率從激光器中提取信號(hào)，電流激發(fā)拉曼散射（SRS）顯微鏡已經(jīng)達(dá)到了散粒噪聲限制的檢測(cè)靈敏度。SRS顯微鏡中基于激光的本振不僅可以產(chǎn)生高水平的信號(hào)，還可以產(chǎn)生較大的散粒噪聲，從而降低圖像質(zhì)量和光譜保真度。在這里，我們展示了一種去噪算法，該算法通過(guò)總變異最小化來(lái)消除空間和光譜域中的噪聲。對(duì)于稀釋的二甲基亞砜溶液，SRS光譜圖像的信噪比提高了57倍，對(duì)于生物組織，SRS光譜圖像的信噪比提高了15倍。最初埋藏在噪聲中的目標(biāo)分子的弱拉曼峰被解開(kāi)。將去噪算法與多變量曲線分辨率相結(jié)合，可以區(qū)分秀麗隱桿線蟲(chóng)中富含蛋白質(zhì)的細(xì)胞器的脂肪儲(chǔ)存?？傊?，我們的方法在沒(méi)有幀平均的情況下顯著提高了檢測(cè)靈敏度，這對(duì)于體內(nèi)光譜成像非常有用。
關(guān)鍵詞：
成像處理?無(wú)標(biāo)記顯微鏡?非線性顯微鏡?拉曼光譜
原文摘要：
High-speed coherent Raman scattering imaging is opening a new avenue to unveiling the cellular machinery by visualizing the spatio-temporal dynamics of target molecules or intracellular organelles. By extracting signals from the laser at MHz modulation frequency, current stimulated Raman scattering (SRS) microscopy has reached shot noise limited detection sensitivity. The laser-based local oscillator in SRS microscopy not only generates high levels of signal, but also delivers a large shot noise which degrades image quality and spectral fidelity. Here, we demonstrate a denoising algorithm that removes the noise in both spatial and spectral domains by total variation minimization. The signal-to-noise ratio of SRS spectroscopic images was improved by up to 57 times for diluted dimethyl sulfoxide solutions and by 15 times for biological tissues. Weak Raman peaks of target molecules originally buried in the noise were unraveled. Coupling the denoising algorithm with multivariate curve resolution allowed discrimination of fat stores from protein-rich organelles in C. elegans . Together, our method significantly improved detection sensitivity without frame averaging, which can be useful for in vivo spectroscopic imaging.
關(guān)鍵詞：
Imaging processing?Label-free microscopy?Non-linear microscopy?Raman spectroscopy
??2 運(yùn)行結(jié)果
?主函數(shù)代碼：
clear all
close all
clc
addpath(genpath('./spectral_tv/'));
sel_exp ? ? = 2; ?% select an experiment (1 or 2)
% Set the number of rows, columns and frames.
M ? ? ? ? ? = 128;
N ? ? ? ? ? = 128;
K ? ? ? ? ? = 50;
% Load a hyperspectral image (DMSO100%)
file_name ? = '../data/DMSO100%.tif';
hyper_true ?= read_hyperdata(file_name, M, N, K);
[rows, cols, frames] = size(hyper_true);
% Add noise in the hyperspectral image
if sel_exp==1
? ? tmp ? ? ? ?= read_hyperdata('../data/DMSO10%.tif', M, N, K);
? ? sigma_true = estimate_noise_level(tmp);
elseif sel_exp==2
? ? sigma_true = 0.005:0.005:(0.005*frames);
end
hyper_noisy = zeros(rows, cols, frames);
for i=1:frames
? ? hyper_noisy(:,:,i) = hyper_true(:,:,i) + sigma_true(i)*randn(rows, cols);
end
% Spectral Total Variation
opts.beta ? = [1 1 0.1];
runtime ? ? = tic;
out_stv ? ? = spectral_tv(hyper_noisy, opts);
runtime_stv = toc(runtime);
sigma_est ? = out_stv.sigma;
psnr_stv ? ?= psnr(hyper_true, out_stv.f);
% Original Total Variation
mu ? ? ? ? ?= 1;
opts.w ? ? ?= mean(out_stv.w(:));
opts.beta ? = [1 1 0.1];
runtime ? ? = tic;
out_tv ? ? ?= deconvtvl2(hyper_noisy, 1, mu, opts);
runtime_tv ?= toc(runtime);
psnr_tv ? ? = psnr(hyper_true, out_tv.f);
% Print PSNRs between true and denoised images.
fprintf('Method: spectral tv, \t psnr: %6.4f, \t runtime: %6.4f\n', psnr_stv, runtime_stv);
fprintf('Method: original tv, \t psnr: %6.4f, \t runtime: %6.4f\n', psnr_tv, runtime_tv);
% Plot the true and estimeated noise level.
if sel_exp==1 || sel_exp==2
? ? figure;
? ? plot(sigma_true, 'LineWidth', 2, 'Color', 'g');
? ? hold on;
? ? plot(sigma_est, 'LineWidth', 2, 'Color', 'r');
? ? hold off;
? ? xlabel('frame');
? ? ylabel('noise standard deviation');
? ? legend('True', 'Estimated', 'Location', 'best');
end
??3?參考文獻(xiàn)
部分理論來(lái)源于網(wǎng)絡(luò)，如有侵權(quán)請(qǐng)聯(lián)系刪除。文章來(lái)源：http://www.zghlxwxcb.cn/news/detail-624794.html
[1] Chien-Sheng Liao, Joon Hee Choi, Delong Zhang, Stanley H. Chan and Ji-Xin Cheng, "Denoising Stimulated Raman Spectroscopic Images by Total Variation Minimization," Journal of Physical Chemistry C, Jul. 2015.文章來(lái)源地址http://www.zghlxwxcb.cn/news/detail-624794.html
??4 Matlab代碼、數(shù)據(jù)、文章
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