Dataset Information

Fluorescence imaging reversion using spatially variant deconvolution.

ABSTRACT: Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a method that is proposed for improving the accuracy and sensitivity achieved. Unlike classical methods that presume a homogeneous spatial distribution of optical properties in tissue, SAIRC explicitly measures the optical heterogeneity in tissues. This information allows, for the first time, the application of spatially-dependent deconvolution to correct the fluorescence images captured in relation to their modification by photon scatter. Using experimental measurements from phantoms and animals, we investigate the improvement in resolution and quantification over non-corrected images. We discuss how the proposed method is essential for maximizing the performance of fluorescence molecular imaging in the clinic.

SUBMITTER: Anastasopoulou M

PROVIDER: S-EPMC6889134 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fluorescence imaging reversion using spatially variant deconvolution.

Anastasopoulou Maria M Gorpas Dimitris D Koch Maximilian M Liapis Evangelos E Glasl Sarah S Klemm Uwe U Karlas Angelos A Lasser Tobias T Ntziachristos Vasilis V

Scientific reports 20191202 1

Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a m ...[more]

PMID: 31792293

Similar Datasets

Project description:Spatial light modulation using cost efficient digital micromirror devices (DMD) is finding broad applications in fluorescence microscopy due to the reduction of phototoxicity and bleaching and the ability to manipulate proteins in optogenetic experiments. However, precise illumination by DMDs and their application to single-molecule localization microscopy (SMLM) remained a challenge because of non-linear distortions between the DMD and camera coordinate systems caused by optical components in the excitation and emission path. Here we develop a fast and easy to implement calibration procedure that determines these distortions and matches the DMD and camera coordinate system with a precision below the optical diffraction limit. As a result, a region from a fluorescence image can be selected with a higher precision for illumination compared to a rigid transformation allowed by manual alignment of the DMD. We first demonstrate the application of our precisely calibrated light modulation by performing a proof of concept fluorescence recovery after photobleaching experiment with the endoplasmic reticulum-localized protein IRE1 fused to GFP in budding yeast (S. cerevisiae). Next, we develop a spatially informed photoactivation approach for SMLM in which only regions of the cell that contain photoactivatable fluorescent proteins are selected for photoactivation. The reduced exposure of the cells to 405 nm light increased the possible imaging time by 44% until phototoxic effects cause a dominant fluorescence background and a change in cell morphology. As a result, the mean number of reliable single-molecule localizations was also significantly increased by 28%. Since the localization precision and the ability for single-molecule tracking is not altered compared to traditional photoactivation of the entire field of view, spatially informed photoactivation significantly improves the quality of SMLM images and single-molecule tracking data. Our precise calibration method therefore lays the foundation for improved SMLM with active feedback photoactivation far beyond the applications in this work.

Dataset Information

Fluorescence imaging reversion using spatially variant deconvolution.

Publications

Fluorescence imaging reversion using spatially variant deconvolution.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets