Restoration of Light Sheet Multi-View Data
generated by a high-NA scanned excitation Bessel beam, and newer developments such as scanning Bessel lattice light sheet microscopy [ 9 ]. These models take into account that the light sheet is not uniform as a function of the distance from the illumination objective to the focus point, compen- sating for the resulting spatial changes in the PSF when
deconvolution is applied ( Figure 1B ). Even modification to the PSF structure from an axial or lateral focus offset can be accounted for by adjusting the corresponding parameters in Huygens ( Figure 2B ).
Figure 5 : Fusion and deconvolution of multiview Gaussian-based LSFM images. Eight rotated views of a fl uorescent Drosophila brain were imaged with a Zeiss Z1 light sheet microscope. All views were fused in Huygens without and with deconvolution. Maximum intensity projections of both fused results show a rescue of signal in regions where the individual views show a degradation (shown in Figure 4B ). The deconvolved and fused result reveals more contrast and object detail in both the NRE-GFP and Bruchpilot channel. Bottom images are magnifi - cations. Scale bars are in micrometers.
Skewing/de-skewing of specific LSFM images . In a few LSFM setups, the excitation and emission axes are oriented at an oblique angle relative to the sample stage ( Figure 3 ). For example, such a setup can be implemented as an add-on module to a standard microscope body. In such systems, the specimen mounted on the stage is scanned horizontally to move the focus through the sample. However, since the scanning does not occur parallel to the optical axis, this leads to a movement in multiple spatial directions. The effect is a shear (skew) in the recorded 3D image stack ( Figure 3 ), thereby complicating deconvolution since the PSF is sheared accordingly. Therefore, the image must first be corrected by shifting all the z -slices back into their correct position ( Figure 3 ). The shift between consecutive z -slices is constant and depends on the step distance of the stage and the objective angle. The Object Stabilizer in Huygens version 18.04 (and later) has been extended with an option to correct for the skewing within a light-sheet image. By entering the step distance and objective angle, the appropriate back-shifts are calculated and applied to each z -slice. After stabilization, the image can be further processed, and deconvolution can be applied as usual.
Figure 6 : Fusion and deconvolution of multiview Gaussian-based LSFM images. Left images show MIPs of the individual channels for Bruchpilot and NRE-GFPs, which are displayed together in Figure 5 . Magnifi cations of both channels are shown as MIPs and single slices. Again more object detail can be recognized when applying deconvolution during the fusion process. Scale bars are in micrometers.
2018 September •
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Correcting additional imaging defects . Aside from restoring blur and noise within LSFM data using deconvo- lution, additional image restoration may be needed to correct for other artifacts common to fluorescence microscopy [ 10 , 11 ]. For example, local charge leakages or dead pixels within the camera chip may result in the presence of hot and cold pixels in images. Also, cross-talk/ bleed-through between channels and lens imperfections cause chromatic aberrations that hamper the correct interpretation and analysis of image data. Specific options within the Huygens software, such as the Hot & Cold Pixel Corrector, Chromatic Aberration Corrector, and CrossTalk Corrector, are present to address these types of distortions in light sheet image data. Huygens Light Sheet Fusion and Deconvolution Wizard . Light sheet fluores- cence microscopy is well suited for imaging large specimens from different directions, either by physically rotating the object itself or by detecting and illuminating from different directions ( Figure 1A ). Such a multi-angle measurement may show specific features more clearly in some of the image stacks than in others. For instance, images from deep layers of the specimen are generally more degraded in quality than images acquired from regions close to the objective because of photon scattering and absorption by the sample material. Thus, by fusing multi-view images into one single image ( Figures 1 A and 4 A), image quality can improve in these regions. Moreover,
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