Polarization-sensitive optical projection tomography for muscle fiber imaging

Polarization contrast optical diffraction tomography

We demonstrate large scale polarization contrast optical diffraction tomography (ODT). In cross-polarized sample arm detection configuration we determine, from the amplitude of the optical wavefield, a relative measure of the birefringence projection. In parallel-polarized sample arm detection configuration we image the conventional phase projection. For off-axis sample placement we observe for polarization contrast ODT, similar as for phase contrast ODT, a strongly reduced noise contribution. In the limit of small birefringence phase shift δ we demonstrate tomographic reconstruction of polarization contrast images into a full 3D image of an optically cleared zebrafish. The polarization contrast ODT reconstruction shows muscular zebrafish tissue, which cannot be visualized in conventional phase contrast ODT. Polarization contrast ODT images of the zebrafish show a much higher signal to noise ratio (SNR) than the corresponding phase contrast images, SNR=73 and SNR=15, respectively.

Gaussian Light Model in Brightfield Optical Projection Tomography

This study focuses on improving the reconstruction process of the brightfield optical projection tomography (OPT). OPT is often described as the optical equivalent of X-ray computed tomography, but based on visible light. The detection optics used to collect light in OPT focus on a certain distance and induce blurring in those features out of focus. However, the conventionally used inverse Radon transform assumes an absolute focus throughout the propagation axis. In this study, we model the focusing properties of the detection by coupling Gaussian beam model (GBM) with the Radon transform. The GBM enables the construction of a projection operator that includes modeling of the blurring caused by the light beam. We also introduce the concept of a stretched GBM (SGBM) in which the Gaussian beam is scaled in order to avoid the modeling errors related to the determination of the focal plane. Furthermore, a thresholding approach is used to compress memory usage. We tested the GBM and SGBM approaches using simulated and experimental data in mono- and multifocal modes. When compared with the traditionally used filtered backprojection algorithm, the iteratively computed reconstructions, including the Gaussian models GBM and SGBM, provided smoother images with higher contrast.

Stripe artifact elimination based on nonsubsampled contourlet transform for light sheet fluorescence microscopy

Stripe artifacts, caused by high-absorption or high-scattering structures in the illumination light path, are a common drawback in both unidirectional and multidirectional light sheet fluorescence microscopy (LSFM), significantly deteriorating image quality. To circumvent this problem, we present an effective multidirectional stripe remover (MDSR) method based on nonsubsampled contourlet transform (NSCT), which can be used for both unidirectional and multidirectional LSFM. In MDSR, a fast Fourier transform (FFT) filter is designed in the NSCT domain to shrink the stripe components and eliminate the noise. Benefiting from the properties of being multiscale and multidirectional, MDSR succeeds in eliminating stripe artifacts in both unidirectional and multidirectional LSFM. To validate the method, MDSR has been tested on images from a custom-made unidirectional LSFM system and a commercial multidirectional LSFM system, clearly demonstrating that MDSR effectively removes most of the stripe artifacts. Moreover, we performed a comparative experiment with the variational stationary noise remover and the wavelet-FFT methods and quantitatively analyzed the results with a peak signal-to-noise ratio, showing an improved noise removal when using the MDSR method.