Polarization imaging-based radiomics approach for the staging of liver fibrosis

Simultaneous detection of polarization states and wavefront by an angular variant micro-retarder-lens array

We have demonstrated simultaneous detection of the polarization states and wavefront of light using a 7 × 7 array of angular variant micro-retarder-lenses. Manipulating the angular variant polarization with our optical element allows us to determine the two-dimensional distribution of polarization states. We have also proposed a calibration method for polarization measurements using our micro-retarder-lens array, allowing accurate detection of polarization states with an ellipticity of ± 0.01 and an azimuth of ± 1.0°. We made wavefront measurements using the micro-retarder-lens array, achieving a resolution of 25 nm. We conducted simultaneous detection of the polarization states and wavefront on four types of structured beam as samples. The results show that the two-dimensional distributions of the polarization states and wavefront for the four types of structured light are radially and azimuthally polarized beams, as well as left- and right-hand optical vortices. Our sensing technology has the potential to enhance our understanding of the nature of light in the fields of laser sciences, astrophysics, and even ophthalmology.

Megahertz detection of spectroscopic polarization by a time-encoded supercontinuum vector beam

We demonstrated a 40-MHz detection of spectroscopic polarization by a supercontinuum vector beam with a wavelength-dependent polarization state. To achieve the high-repetition-rate measurement, we detected the rotation angle of polarization and the spectrum by measuring the temporal waveform using a photodetector after expanding the pulse duration of the supercontinuum vector beam. The spectrum of the supercontinuum vector beam was measured using a spectrometer. We compared it with the temporal waveforms, confirming a good agreement of spectra between the conventional spectrometer and the temporal waveforms. The detection method is useful for many applications requiring high-repetition-rate spectroscopic-polarization measurements, such as the defect inspection of thin optical materials.

Mueller matrix imaging of pathological slides with plastic coverslips

Mueller matrix microscopy is capable of polarization characterization of pathological samples and polarization imaging based digital pathology. In recent years, hospitals are replacing glass coverslips with plastic coverslips for automatic preparations of dry and clean pathological slides with less slide-sticking and air bubbles. However, plastic coverslips are usually birefringent and introduce polarization artifacts in Mueller matrix imaging. In this study, a spatial frequency based calibration method (SFCM) is used to remove such polarization artifacts. The polarization information of the plastic coverslips and the pathological tissues are separated by the spatial frequency analysis, then the Mueller matrix images of pathological tissues are restored by matrix inversions. By cutting two adjacent lung cancer tissue slides, we prepare paired samples of very similar pathological structures but one with a glass coverslip and the other with a plastic coverslip. Comparisons between Mueller matrix images of the paired samples show that SFCM can effectively remove the artifacts due to plastic coverslip.

Analyzing the Influence of Imaging Resolution on Polarization Properties of Scattering Media Obtained From Mueller Matrix

The Mueller matrix contains abundant micro- and even nanostructural information of media. Especially, it can be used as a powerful tool to characterize anisotropic structures quantitatively, such as the particle size, density, and orientation information of fibers in the sample. Compared with unpolarized microscopic imaging techniques, Mueller matrix microscopy can also obtain some essential structural information about the sample from the derived parameters images at low resolution. Here, to analyze the comprehensive effects of imaging resolution on polarization properties obtained from the Mueller matrix, we, first, measure the microscopic Mueller matrices of unstained rat dorsal skin tissue slices rich in collagen fibers using a series of magnifications or numerical aperture (NA) values of objectives. Then, the first-order moments and image texture parameters are quantified and analyzed in conjunction with the polarization parameter images. The results show that the Mueller matrix polar decomposition parameters diattenuation D, linear retardance δ, and depolarization Δ images obtained using low NA objective retain most of the structural information of the sample and can provide fast imaging speed. In addition, the scattering phase function analysis and Monte Carlo simulation based on the cylindrical scatterers reveal that the diattenuation parameter D images with different imaging resolutions are expected to be used to distinguish among the fibrous scatterers in the medium with different particle sizes. This study provides a criterion to decide which structural information can be accurately and rapidly obtained using a transmission Mueller matrix microscope with low NA objectives to assist pathological diagnosis and other applications.

Spatial and temporal patterns in dynamic-contrast enhanced intraoperative fluorescence imaging enable classification of bone perfusion in patients undergoing leg amputation

Dynamic contrast-enhanced fluorescence imaging (DCE-FI) classification of tissue viability in twelve adult patients undergoing below knee leg amputation is presented. During amputation and with the distal bone exposed, indocyanine green contrast-enhanced images were acquired sequentially during baseline, following transverse osteotomy and following periosteal stripping, offering a uniquely well-controlled fluorescence dataset. An unsupervised classification machine leveraging 21 different spatiotemporal features was trained and evaluated by cross-validation in 3.5 million regions-of-interest obtained from 9 patients, demonstrating accurate stratification into normal, suspicious, and compromised regions. The machine learning (ML) approach also outperformed the standard method of using fluorescence intensity only to evaluate tissue perfusion by a two-fold increase in accuracy. The generalizability of the machine was evaluated in image series acquired in an additional three patients, confirming the stability of the model and ability to sort future patient image-sets into viability categories.