Koos Krisztian, Molnár József, Kelemen Lóránd, Tamás Gábor, Horvath Peter
Synthetic and Systems Biology Unit, Hungarian Academy of Sciences, BRC, Szeged, Hungary.
Institute of Biophysics, Hungarian Academy of Sciences, BRC, Szeged, Hungary.
Sci Rep. 2016 Jul 25;6:30420. doi: 10.1038/srep30420.
Label-free microscopy techniques have numerous advantages such as low phototoxicity, simple setup and no need for fluorophores or other contrast materials. Despite their advantages, most label-free techniques cannot visualize specific cellular compartments or the location of proteins and the image formation limits quantitative evaluation. Differential interference contrast (DIC) is a qualitative microscopy technique that shows the optical path length differences within a specimen. We propose a variational framework for DIC image reconstruction. The proposed method largely outperforms state-of-the-art methods on synthetic, artificial and real tests and turns DIC microscopy into an automated high-content imaging tool. Image sets and the source code of the examined algorithms are made publicly available.
无标记显微镜技术具有许多优点,如光毒性低、设置简单,无需荧光团或其他造影材料。尽管具有这些优点,但大多数无标记技术无法可视化特定的细胞区室或蛋白质的位置,并且图像形成限制了定量评估。微分干涉对比(DIC)是一种定性显微镜技术,可显示标本内的光程长度差异。我们提出了一种用于DIC图像重建的变分框架。该方法在合成、人工和实际测试中大大优于现有方法,并将DIC显微镜转变为一种自动化的高内涵成像工具。所研究算法的图像集和源代码已公开提供。