SignificanceMueller matrix imaging (MMI) is a comprehensive form of polarization imaging useful for assessing structural changes. However, there is limited literature on the polarimetric properties of brain specimens, especially with multispectral analysis.AimWe aim to employ multispectral MMI for an exhaustive polarimetric analysis of brain structures, providing a reference dataset for future studies and enhancing the understanding of brain anatomy for clinicians and researchers.ApproachA multispectral wide-field MMI system was used to measure six fresh lamb brain specimens. Multiple decomposition methods (forward polar, symmetric, and differential) and polarization invariants (indices of polarimetric purity and anisotropy coefficients) have been calculated to obtain a complete polarimetric description of the samples. A total of 16 labels based on major brain structures, including grey matter (GM) and white matter (WM), were identified. K-nearest neighbors classification was used to distinguish between GM and WM and validate the feasibility of MMI for WM identification.ResultsAs the wavelength increases, both depolarization and retardance increase, suggesting enhanced tissue penetration into deeper layers. Moreover, utilizing multiple wavelengths allowed us to track dynamic shifts in the optical axis of retardance within the brain tissue, providing insights into morphological changes in WM beneath the cortical surface. The use of multispectral data for classification outperformed all results obtained with single-wavelength data and provided over 95% accuracy for the test dataset.ConclusionsThe consistency of these observations highlights the potential of multispectral wide-field MMI as a non-invasive and effective technique for investigating the brain’s architecture.
In this study, we applied Multispectral Mueller Matrix Imaging (MMI) at six distinct wavelengths in the visible range to analyze brain structures using lamb cerebral samples. The imaging of several brain sections revealed that white matter (WM) exhibits pronounced depolarization and retardance when contrasted with grey matter (GM), a phenomenon likely attributed to the elevated scattering and anisotropic nature of WM. More precisely, with an increase in wavelength, both depolarization and retardance also increase, suggesting additional penetration into deeper tissue layers. Employing various wavelengths enabled us to trace the shifts in the optical axis of retardance within the brain tissue, offering insights into the morphological changes in WM and GM below the cortical surface. The consistency observed in our results highlights the promise of Multispectral Wide-Field MMI as a non-intrusive, efficacious modality for probing brain architecture.
Structured light 3D surface imaging reconstructs the 3D surface shape of an object by analyzing the deformation of a projected structured-light pattern. The detection of the pattern is a crucial step in this technique, which can be affected by the blurring of the patterns due to tissue scattering and absorbing. In this study we experimentally investigate how the projected structured light based on hyperspectral projection. A hyperspectral projector is constructed to generate patterns of different wavelengths, bandwidth and densities. The projected structured light is tested on porcine tissue in vitro. The sharpness of all the patterns and property of tissue are evaluated. The results indicate that tissue-dependent wavelength of light with appropriate density of pattern yield optimal illumination which corresponds to 3D reconstruction accuracy for structured light 3D endoscopy.
Multispectral endoscopic imaging is a promising technique for lesion detection, and surgical guidance. Based on different spectral properties of tissues, multispectral imaging can provide enhanced contrast of vascular structures (narrow band imaging) or enable the quantitative analysis of hemoglobin and lipid. The multiparameter phantoms serve as efficient tools for system calibration, performance evaluation, and algorithm development in multispectral endoscopy are needed. In this paper, we developed a multiparameter tissue-mimicking phantom that mimics the parameters of human gastric mucosa, such as scattering coefficient, scattering layer thickness, vascular width, lipid on the surface and blood oxygen saturation (SO2). We verified the SO2 measurement accuracy by comparing with commercial i-STAT devices for SO2 distribution imaging. At the same time, the segmentation of lipid regions was also tested. Our results demonstrate that this multiparameter phantom is a versatile tool that can facilitate validation and evaluation of multispectral endoscopic systems.
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