The resolution and the field-of-view (FOV) of the Mueller microscope are mutually limiting. The increasing magnification exponentially reduces the FOV of microscopic images, which hinders the acquisition of high-resolution Mueller polarization images with large FOV. To address this problem, we propose a scanning splice method for the Mueller microscope. In this method, an optimized image stitching arithmetic, which specially restricts the selection of feature points to ensure the consistency of stitching results of multiple groups of images with the same position and different polarization states, is combined with Mueller polarization detection techniques. In addition, the combination involved can correct the slight jitter error of the system caused by the rotation of the wave plate during Mueller polarization detection. The experiment results demonstrate that this optimized arithmetic is more accurate than the traditional image stitching arithmetic. This research provides the possibility of the development of the whole slide scanning Mueller microscope.
Star test polarimeter can map the polarization state of incident light into an intensity distribution of the detection plane
by placing a space-variant phase retarder (SVPR) in the pupil plane of an optical system, which can achieve fast
acquisition of polarization information of incident light from a single irradiance image. However, subjected by the
system’s alignment and vibration, star test polarimetry need the calibration scheme with high robustness and fast speed.
This paper develops a fast calibration method for Star test polarimetry by measuring three intensity distribution of
orthogonal polarization state and an intensity distribution of left-handed circular polarization. Experimental results show
that the proposed method, combined with normalized least square (NLS), can rapidly calibrate the theoretical model to
accurately measure the polarization state of incident light.
Mueller matrix polarimetry is regarded as a promising technique to comprehensively provide the optical and
microstructural information of tissues. Especially, for pathological diagnosis, the Mueller matrix imaging can be used as a
powerful tool to detect the structural features of abnormal tissue areas on pathological sections. However, a comparative
study of the polarization characteristics of pathological sections with different preparation state is still needed to help
decide which kinds of sections can be effectively used for polarization imaging diagnosis. In this paper, we apply the
Mueller imaging polarimeter for quantitative detection of lung cancer section with the state of undewaxed, dewaxed and H-E
stained at cellular-level respectively. The Mueller matrix polar decomposition parameters of the lung cancer section are
calculated and analyzed. The results indicate that the polarization images of undewaxed section can reflect the
morphology and arrangement of cells. The polarization images of dewaxed is more suitable for the quantitative analysis
of tissue. The polarization images of stained sections are sensitive to the nucleus, which is suitable for the study of the
internal structure of the nucleus.
Mueller polarization imaging technology can fully reflect the polarization characteristics of the sample, and can be used
as a method for imaging thin pathological sections of collagen tissue samples. So far, there has been no actual publication
about the detection of transplanted tendons using Mueller matrix imaging technology. In this paper, we apply the Mueller
imaging polarimeter for quantitative detection of rabbit transplanted tendon samples with or without tenocytes. The polar
decomposition parameters of the Mueller matrix of the rabbit tendon tissues are calculated and analyzed. Quantitative
analysis showed that tenocytes caused the decrease of tendon fibers retardance and the increase of standard deviation of
tendon fibers orientation. The experimental results indicate that the retardance and the orientation angle parameters of the
Mueller matrix can be used as quantitative indicators to distinguish rabbit tendon tissues with or without tenocytes and
can reveal the structural characteristics of collagen fiber bundles, which may provide more useful information for the
evaluation of tendon transplantation.
Mueller matrix polarization imaging system (MMPIS) is one of the most prospective tools that can provide a highresolution image of polarization properties for samples or systems. The MMPIS is composed of a laser source, polarization state generator (PSG), the sample, polarization state analyzer (PSA), a high-resolution imaging optics, collimating optics, and a CCD camera. Usually, the traditional eigenvalue calibration method (ECM) can be used to calibrate PSG and PSA. However, the imaging and collimating optics are not calibrated in MMPIS. For the highnumerical-aperture imaging system, the imaging and collimating optics can behave as polarization aberration modifying the tested sample’s polarization properties leading to the erroneous judgment which affects the measurement accuracy of the MMPIS. In this paper, the multi-step eigenvalue calibration method (MECM) is explored to calibrate MMPIS. For the MECM applied to calibrate MMPIS, the calibration samples are required to place in different positions of the light path and the ECM is adopted in each position. In this way, the Mueller matrices of PSG and PSA, as well as the Mueller matrices of imaging optics and collimating optics can be obtained through calculation. To evaluate the measurement accuracy of MMPIS, the sample with known polarization properties such as air is measured. The experimental results show that before calibrating the imaging optics and collimating optics the measurement accuracy of MMPIS is 0.0124, while after the measurement accuracy has been improved to 0.0046, which is 62.90% better than before. The MECM can be used for the requirements of high accuracy measurement.
Mueller matrix images(MMI) contain complete polarization information of the media. Mueller matrix decomposition technique, where Mueller matrix polar decomposition(MMPD) and differential decomposition(MMDD) are widely used to decompose MMI, is the key to extract intrinsic polarimetry characteristics of biological tissues. For the decomposition of biological tissue MMI, Satish et al. expressed that MMDD was more suitable for Mueller matrix polarimetric analysis of tissues, while Alali et al. pointed out that MMDD did not offer a great advantage over MMPD. To deal with this problem, we explore how to choose the appropriate decomposition method to accurately extract the polarization information in biological tissues. The experimental results indicate that the linear retardance and optical rotation images obtained from two decomposition methods are different if tissues exhibit significant linear retardance and optical rotation effects simultaneously. According to the physical model of MMDD that the occurrence of polarization effects is orderindependent, MMDD should be applied to MMI of tissues to obtain accurate polarization characteristics in this situation. The biological tissue has low optical rotation in most cases in which the polarimetric images extracted from two decomposition methods are nearly identical, so MMPD and MMDD both can accurately acquire the polarimetric properties of tissues. Meanwhile, comparing the runtime of two decomposition methods to process MMI, we find the processing speed of MMDD is much faster than MMPD. Thus, we summarize that MMDD method is more suitable for the decomposition of the biological tissue MMI, with the advantages of both fast and accurate, which is significant in diagnosis of clinical.
Channeled spectropolarimeter (CSP) measures the spectrally resolved Stokes vector of light from only one single spectral acquisition, which makes it possible to accurately measure dynamic events. The accurate reconstruction of Stokes vector plays a key role in this snapshot technique shifting the main burden of measurement to computational work. The state-ofthe-art algorithm runs the Fourier transform of the channeled spectrum or linear operator model of the system and its pseudo-inverse to reconstruct Stokes vector. However, they may suffer from the lack of signal-to-noise ratio (SNR) then reduce the accuracy of reconstruction. To accurately reconstruct Stokes vector from noise-contaminated data, we propose an effective method called fast compressed channeled spectropolarimeter (FCCSP). In our FCCSP method, the spectrum from spectrometer is seen as the compressive representation of Stokes vector, thus the FCCSP algorithm is to solve an underdetermined problem, where we reconstruct the 4N×1 Stokes vector from only N×1 spectral data acquisition points. Simulation results show that our FCCSP method is more accurate to reconstruct Stokes vector changing gradually with wavelength from noise-contaminated spectrum than Fourier and linear operator methods. Besides, it is faster and more memory and computation-friendly than other compressed CSP method.
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