Extended dynamic range imaging for noise mitigation in fluorescence anisotropy imaging

Abstract

Significance: Fluorescence polarization (FP) and fluorescence anisotropy (FA) microscopy are powerful imaging techniques that allow to translate the common FP assay capabilities into the in vitro and in vivo cellular domain. As a result, they have found potential for mapping drugprotein or protein-protein interactions. Unfortunately, these imaging modalities are ratiometric in nature and as such they suffer from excessive noise even under regular imaging conditions, preventing accurate image-feature analysis of fluorescent molecules behaviors. Aim: We present a high dynamic range (HDR)-based FA imaging modality for improving image quality in FA microscopy. Approach: The method exploits ad hoc acquisition schemes to extend the dynamic range of individual FP channels, allowing to obtain FA images with increased signal-to-noise ratio. Results: A direct comparison between FA images obtained with our method and the standard, clearly indicates how an HDR-based FA imaging approach allows to obtain high-quality images, with the ability to correctly resolve image features at different values of FA and over a substantially higher range of fluorescence intensities. Conclusion: The method presented is shown to outperform standard FA imaging microscopy narrowing the spread of the propagated error and yielding higher quality images. The method can be effectively and routinely used on any commercial imaging system and could be also translated to other microscopy ratiometric imaging modalities.

A rapid denoised contrast enhancement method digitally mimicking an adaptive illumination in submicron-resolution neuronal imaging

“…In such an approach, a feedback mechanism is utilized which monitors the emerging signal strength and accordingly provides suitable feedback to a tunable excitation source to regulate the excitation power (Ji et al, 2008;Yang et al, 2017;Chu et al 2007Chu et al , 2010Hoebe et al, 2007). Another approach is to employ a real-time high dynamic range (HDR) imaging (Vinegoni et al, 2016(Vinegoni et al, , 2019Feruglio et al, 2020), which collects multiple low dynamic range (LDR) images over multiple optically-separated detection channels, and subsequently fuse them together to form the HDR image. However, implementing these techniques requires dedicated hardware configurations.…”

Real-time Noise-suppressed Wide-Dynamic-Range Compression in Ultrahigh-Resolution Neuronal Imaging

“…In such an approach, a feedback mechanism is utilized which monitors the emerging signal strength and accordingly provides a suitable feedback to a tunable excitation source to regulate the excitation power [17][18][19][20][21]. Another approach is to employ a real-time high-dynamic-range (HDR) imaging [22][23][24], which collects multiple lowdynamic-range (LDR) images over multiple optically-separated detection channels, and subsequently fuses them together to form the HDR image. However, implementing these techniques requires dedicated hardware configurations.…”