Methods to reduce or remove background (BG) signal
Depending on the way in which the BG caused by a out-of-focus-signal is handled, we distinguish between exclusive and inclusive methods.
Inclusive methods, such as widefield (WF) deconvolution microscopy, take the distribution of light in the whole volume into account and reassign recorded photons from the BG to their origins, thereby increasing the SNR of the recorded volumes. This reassignment can be done, because the distribution of light originating from a single point is described by the Point Spread Function (PSF). Inclusive methods reach their limits as more and more light from out-of-focus layers is combined with the light from the in-focus-region. Effects which distort the PSF, such as light scattering, increase the BG, making restoration with inclusive methods more difficult. Unfortunately, scattering is unavoidable in biological specimens. Because inclusive methods, according to their definition, use all signals detected in the image, they also process signal components from out-of-focus layers that should not contribute to the final result.
Exclusive methods are based on the principle of separating out the unwanted BG and subtracting it from the image, so only the signal from the in-focus layer remains. Camera-based systems utilize hardware to prevent the acquisition of out-of-focus light (e.g. spinning disk systems or selective plane illumination) or a combination of software and hardware to remove BG components (grid projecting systems). Grid projecting systems need multiple images to be acquired, which can lead to motion artefacts when recording fast moving samples. In addition, they work only up to a limited depth, as a sharp image of the grid needs to be detected by the camera. The gold standard in removing out-of-focus BG are pinhole-based scanning systems. The pinhole of a confocal system excludes light from out-of-focus layers, so only light from the in-focus layer reaches the detector. THUNDER Imagers use Computational Clearing as exclusive method to remove the BG with a single recorded image in real time. It therefore overcomes the disadvantages when imaging life samples as mentioned above.
Computational Clearing (CC)
Computational Clearing is the core technology in THUNDER Imagers. It detects and removes the out-of-focus BG for each image, making the signal of interest directly accessible. At the same time, in the in-focus area, edges, and intensity of the specimen features remain. When recording an image with a camera-based fluorescence microscope the “unwanted” BG adds to the “wanted” signal of the in-focus structures and both is always recorded. For best results, the aim is to reduce the BG as much as possible. To exclude unwanted BG from an image, it is critical to find key criteria necessary to accurately separate the BG from the wanted signal. Generally, BG shows a characteristic behavior in recorded images which is independent of its origin. Hence, just from its appearance in an image, it is not discernable where the BG comes from. Specifically in biological samples, the BG is usually not constant. It is quite variable over the field of view (FOV). Computational Clearing takes this automatically into account to make the in-focus signal immediately accessible.
Images acquired with a widefield microscope can be decomposed into two components: in-focus and BG signals. BG is mainly arising from out-of- focus signals. Thus, a widefield image, I(r), can approximately be given by:
Where psfof/if(r) and f(r) are the effective point spread functions of the in-focus (if) and out-of-focus (of) contributions and the fluorophore distribution, respectively. Because the out-of-focus PSF is much wider than the in-focus one, these two contributions in Eq. (1) can be clearly separated by length-scale-discriminating algorithms, such as, wavelet transforms. We developed an iterative algorithm to separate these two contributions. It calculates the following minimization for each iteration:
Here S[ ̂Iout] represents the structural length scale of the estimated out of focus contribution Iout. The structural length scale r0 Eq. (2) is calculated based on the optical parameters of the system and can be adapted. In the