Development of a new polarized hyperspectral imaging microscope

Zhou, Ximing; Ma, Ling; Halicek, Martin; Dormer, James D.; Fei, Baowei

doi:10.1117/12.2549676

Cited by 7 publications

(10 citation statements)

References 25 publications

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“…The setup of our home-made polarized hyperspectral microscope has been reported by us previously [28]. The system is capable of full Stokes polarized light hyperspectral imaging, which acquires the images of four Stokes vector parameters (S0, S1, S2, and S3) in the wavelength range between 467 nm and 750 nm.…”

Section: Polarized Hyperspectral Imagingmentioning

confidence: 99%

“…It can acquire the 2D spatial polarization information of the tissue, which reflects various physical properties of the tissue, including surface texture, surface roughness, and surface morphology information [18,19,20,21,22]. The categories of polarized light imaging techniques, namely linear polarization imaging [23,24,25], Muller matrix imaging [26,27], and Stokes vector imaging [28], have been applied on head and neck cancer detection. An orthogonal polarization spectral (OPS) imaging method, which is a type of linear polarization imaging method, was implemented for the evaluation of anti-vascular tumor treatment and oral squamous cell carcinoma on tissue [23,24].…”

Section: Introductionmentioning

confidence: 99%

“…Researchers also adopted a 3×3 Muller Matrix imaging method for oral cancer detection [26]. In our previous study, we developed a polarized hyperspectral imaging microscope, which is able to distinguish squamous cell carcinoma from normal tissue on hematoxylin and eosin (H&E) stained slides from larynx based on the spectra of Stokes vector [28].…”

Section: Introductionmentioning

confidence: 99%

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Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma

Zhou

Mubarak²,

Ma³

et al. 2023

Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2023

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We developed a polarized hyperspectral microscope to collect four types of Stokes vector data cubes (S0, S1, S2, and S3) of the pathologic slides with head and neck squamous cell carcinoma (HNSCC). Our system consists of an optical light microscope with a movable stage, two polarizers, two liquid crystal variable retarders (LCVRs), and a SnapScan hyperspectral camera. The polarizers and LCVRs work in tandem with the hyperspectral camera to acquire polarized hyperspectral images. Synthetic pseudo-RGB images are generated from the four Stokes vector data cubes based on a transformation function similar to the spectral response of human eye for the visualization of hyperspectral images. Collagen is the most abundant extracellular matrix (ECM) protein in the human body. A major focus of studying the ECM in tumor microenvironment is the role of collagen in both normal and abnormal function. Collagen tends to accumulate in and around tumors during cancer development and growth. In this study, we acquired images from normal regions containing normal cells and collagen fibers and from tumor regions containing cancerous squamous cells and collagen fibers on HNSCC pathologic slides. The preliminary results demonstrated that our customized polarized hyperspectral microscope is able to improve the visualization of collagen on HNSCC pathologic slides under different situations, including thick fibers of normal stroma, thin fibers of normal stroma, fibers of normal muscle cells, fibers accumulated in tumors, fibers accumulated around tumors. Our preliminary results also demonstrated that the customized polarized hyperspectral microscope is capable of extracting the spectral signatures of collagen based on Stokes vector parameters and can have various applications in pathology and oncology.

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Section: Polarized Hyperspectral Imagingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma

Zhou

Mubarak²,

Ma³

et al. 2023

Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2023

Self Cite

View full text Add to dashboard Cite

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“…Polarized hyperspectral imaging (PHSI) combines polarized light imaging with HSI to acquire the polarization state, spectrum, and spatial information of a sample. We have previously used PHSI combined with machine learning to detect head and neck cancer on tissue slides [29,30,31].…”

Section: Introductionmentioning

confidence: 99%

Polarized hyperspectral microscopic imaging for white blood cells on Wright-stained blood smear slides

Zhou

Mubarak

et al. 2023

Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2023

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White blood cells, also called leukocytes, are hematopoietic cells of the immune system that are involved in protecting the body against both infectious disease and foreign invaders. The abnormal development and uncontrolled proliferation of these cells can lead to devastating cancers. Their timely recognition in the peripheral blood is critical to diagnosis and treatment. In this study, we developed a microscopic imaging system for improving the visualization of white blood cells on Wright’s stained blood smear slides, with two different setups: polarized light imaging and polarized hyperspectral imaging. Based on the polarized light imaging setup, we collected the RGB images of Stokes vector parameters (S0, S1, S2, and S3) of five types of white blood cells (neutrophil, eosinophil, basophil, lymphocyte, and monocyte), and calculated the Stokes vector derived parameters: the degree of polarization (DOP), the degree of linear polarization (DOLP), and the degree of circular polarization (DOCP). Based on the polarized hyperspectral imaging setup, we also calculated Stokes vector data. The preliminary results demonstrate that Stokes vector derived parameters (DOP, DOLP, and DOCP) could improve the visualization of granules in granulocytes (neutrophils, eosinophils, and basophils). Furthermore, Stokes vector derived parameters (DOP, DOLP, and DOCP) could improve the visualization of surface structures (protein patterns) of lymphocytes enabling subclassification of lymphocyte subpopulations. Finally, S2, S3, and DOCP could improve the visualization of morphology on nucleus of monocytes. We also demonstrated that the polarized hyperspectral imaging setup could provide complementary spectral information to the spatial information on different Stokes vector parameters of white blood cells. This work demonstrates that polarized light imaging and polarized hyperspectral imaging has the potential to become a strong imaging tool in the diagnosis of disorders arising from white blood cells.

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“…Although the randomness of tissue structures has a fast depolarization effect as the polarized light propagates in tissues, certain tissues or cell structures can preserve the degree of polarization detectable 7 , making it a useful optical property for tissue analysis. In intensity-based polarimetry, Stokes vector is a commonly used representation of a light beam, which can be determined by four independent measurements, namely IH, IV, I45, and IRC (or ILC) [8][9][10] . The four elements are the light intensities measured with a horizontal linear analyzer, a vertical linear analyzer, a +45-degree oriented linear analyzer, and a right (or left) circular analyzer in front of the detector, respectively.…”

Section: Introductionmentioning

confidence: 99%

Automated polarized hyperspectral imaging (PHSI) for ex-vivo and in-vivo tissue assessment

Ma¹,

Srinivas²,

Krishnamurthy³

et al. 2023

Label-Free Biomedical Imaging and Sensing (LBIS) 2023

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Polarized light interactions with biological tissues can reveal information regarding tissue structure, while spectral characteristics are closely related to tissue composition. An integration of both modalities in a compact system could better assist tissue assessment. This study aims to develop a polarized hyperspectral imaging (PHSI) system that fulfills both linearly and circularly polarized hyperspectral imaging for in vivo and ex vivo applications. The system is comprised of a white LED, two linear polarizers, two liquid crystal variable retarders (LCVRs), and a hyperspectral snapshot camera. The system was calibrated to compute the full Stokes polarimetry. For tissue differentiation, fresh ex vivo mouse tissue specimens from kidney, liver, spleen, muscle, lung, and salivary gland of mice were imaged. The spectra of three features, named degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP), were generated. A k-nearest neighbor (k-NN) classifier was trained with multi-class spectra and 5-fold cross validation. It was found that DOP better differentiates tissue with an average accuracy of 0.87. Additionally, support vector machine (SVM) classifiers were trained to differentiate between each two of the organs, and it was determined that DOLP better identified kidney, liver, and spleen, whereas DOCP better identified muscle and lung tissues. Then, the setup was employed to image in vivo human fingers with and without a blood occlusion to qualitatively estimate oxygen saturation. Preliminary results demonstrate that both DOLP and DOCP reveal a distinction of oxygen saturation states. These results demonstrate the feasibility of the PHSI system for distinguishing between optical properties of tissues, which has the potential to reveal disease-related information for diverse medical applications.

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Development of a new polarized hyperspectral imaging microscope

Cited by 7 publications

References 25 publications

Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma

Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma

Polarized hyperspectral microscopic imaging for white blood cells on Wright-stained blood smear slides

Automated polarized hyperspectral imaging (PHSI) for ex-vivo and in-vivo tissue assessment

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