Mueller polarimetric imaging for surgical and diagnostic applications: a review

Abstract

Polarization is a fundamental property of light and a powerful sensing tool that has been applied to many areas. A Mueller matrix is a complete mathematical description of the polarization characteristics of objects that interact with light, and is known as a transfer function of Stokes vectors which characterise the state of polarization of light. Mueller polarimetric imaging measures Mueller matrices over a field of view and thus allows for visualising the polarization characteristics of the objects. It has emerged as a promising technique in recent years for tissue imaging, improving image contrast and providing a unique perspective to reveal additional information that cannot be resolved by other optical imaging modalities. This review introduces the basis of the Stokes-Mueller formulism, interpretation methods of Mueller matrices into fundamental polarization properties, polarization properties of biological tissues, and considerations in the construction of Mueller polarimetric imaging devices for surgical and diagnostic applications, including primary configurations, optimization procedures, calibration methods as well as the instrument polarization properties of several widelyused biomedical optical devices. The paper also reviews recent progress in Mueller polarimetric endoscopes and fibre Mueller polarimeters, followed by the future outlook in applying the technique to surgery and diagnostics. Tissue polarization properties convey morphological, micro-structural and compositional information of tissue with great potential for label free characterization of tissue pathological changes. Recent progress in tissue polarimetric imaging and polarization resolved endoscopy paved the way for translation of polarimetric imaging to surgery and tissue diagnosis.

Mapping of retardance, diattenuation and polarizance vector on Poincare sphere for diagnosis and classification of cervical precancer

“…Various imaging techniques, primarily based on transmission, absorption, reflection, spontaneous emission and scattering in light‐tissue interactions, have shown to be responsive to a number of subtle alterations in various diseased tissue. Mueller matrix (MM) polarimetric imaging based on the acquisition of 16 images has shown tremendous potential in precancer detection since the last decade and is best suited for a complete characterization of the biological specimen . These MM images are further processed to extract the essential optical parameters, namely, diattenuation, retardation and depolarization through Lu‐Chipman decomposition method .…”

Learning to classify materials using Mueller imaging polarimetry

“…Mueller polarimetry 1 allows one to measure the polarization properties of a medium. Such measurements, coupled with machine learning techniques, have found successful applications in e.g., biomedical diagnosis, 2,3 car detection 4 or material classication.…”

Distinguishing structural features between Crohn's disease and gastrointestinal luminal tuberculosis using Mueller matrix derived parameters

“…Mueller matrix polarimetry is regarded as a promising technique to provide the optical and microstructural information of tissues comprehensively [9][10][11][12]. Especially, for pathological diagnosis, the Mueller matrix imaging can be used as a powerful tool to detect the structural features of abnormal tissue areas without any exogenous contrast agents [12][13][14].…”

“…Mueller matrix polarimetry is regarded as a promising technique to provide the optical and microstructural information of tissues comprehensively [9][10][11][12]. Especially, for pathological diagnosis, the Mueller matrix imaging can be used as a powerful tool to detect the structural features of abnormal tissue areas without any exogenous contrast agents [12][13][14]. Recently, there are several Mueller matrix analyzing methods such as the Mueller matrix polar decomposition (MMPD) and Mueller matrix transformation (MMT) have been proposed to provide groups of quantitative parameters [15][16][17][18][19].…”