Group-Sparsity-Based Super-Resolution Dipole Orientation Mapping

作者：Long Chen, Miaoyan Wang, Xu Zhang, Michael Zhang, Yucheng Hu, Zuoqiang Shi, Peng Xi, Juntao Gao · 发表于：IEEE Transactions on Medical Imaging · 年份：2019 · DOI：10.1109/tmi.2019.2910221 · 被引用次数：9 · 研究领域：Advanced Fluorescence Microscopy Techniques、Digital Holography and Microscopy、Optical Coherence Tomography Applications

The dipole orientation of fluorophores could be resolved by fluorescence polarization microscopy (FPM), which in turn reveals structural specificity for the labeled organelles. Conventional FPM can detect only the averaged fluorescence anisotropy collected from dipoles within the diffraction-limited volume. Super-resolution dipole orientation mapping (SDOM) method, which applies sparse deconvolution and least square estimation to fluorescence polarization modulation data, achieves the dipole orientation measurement within a sub-diffraction focal area. However, during SDOM analysis, some pixels with fluorescence signal are not resolved with orientation for relatively small adjusted R2. Here we report group-sparsity-based SDOM (GS-SDOM), which utilizes the relevance of modulation sequences to effectively improve the SDOM reconstruction model. More credible resolved dipole orientations with higher adjusted R2can be mapped and false positive estimation for local dipole orientation is vitally corrected. In addition to achieving the same spatial super-resolution as SDOM does, GS-SDOM accesses more morphological information with more credible orientations and more accurate local dipole distribution estimation. During the GS-SDOM analysis of actin filaments in mammalian kidney cells, the dipole orientation of fluorescence is detected always parallel to the direction of the actin filaments. Also with dipole orientation information extracted by GS-SDOM, the reconstructed visual circle ...