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Prof. Alex Vitkin | Seeing the Invisible: How Polarized Light Contributes to Our Understanding and Detection of Cancer

Дата публикации: 11-06-2026 11:53:14

Prof. Alex Vitkin | Seeing the Invisible: How Polarized Light Contributes to Our Understanding and Detection of Cancer
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Light is something we encounter every day, so familiar that it rarely inspires a second thought. Yet beneath its apparent simplicity lies a remarkable complexity. Light can carry information in its brightness and color, but also in its polarization and phase, subtle properties that describe how its waves oscillate and interact. For decades, these hidden dimensions of light have remained largely untapped in medicine. Now, a growing body of research is beginning to reveal their extraordinary potential.
Prof. Alex Vitkin | Seeing the Invisible: How Polarized Light Contributes to Our Understanding and Detection of Cancer
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About this episode

Light is something we encounter every day, so familiar that it rarely inspires a second thought. Yet beneath its apparent simplicity lies a remarkable complexity. Light can carry information in its brightness and color, but also in its polarization and phase, subtle properties that describe how its waves oscillate and interact. For decades, these hidden dimensions of light have remained largely untapped in medicine. Now, a growing body of research is beginning to reveal their extraordinary potential. More

Original article reference

This Audio is based on the papers “In vivo tumor imaging of pre-clinical models via reflection-mode measurements of circular degree of polarization,” in Journal of Biomedical Optics, https://doi.org/10.1117/1.JBO.30.S3.S34105, “Polarized Light Backscattering From Turbid Media: Why Do Rayleigh Scatterers Preserve Linear Polarization More Than Circular Polarization?” in Laser & Photonics Reviews, https://doi.org/10.1002/lpor.202501487, “Laser speckle size and contrast investigation of volumetric scattering from controlled turbid phantoms and mouse skin tissues,” in iScience, https://doi.org/10.1016/j.isci.2025.112433 and “Machine learning-based prediction of luminal breast cancer subtypes using polarised light microscopy,” in British Journal of Cancer, https://doi.org/10.1038/s41416-025-03150-x

Funding

This research was supported by funding from the Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada and the New Frontiers in Research Fund.

Contact

For further information, please contact Carla Kulscar at carla.kulcsar@mail.utoronto.ca

This work is licensed under a Creative Commons Attribution 4.0 International LicenseCreative Commons License

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