Abstract: Methods for improved imaging of internal tissue structures, such as lesions in the peritoneum, are disclosed employing color-weighted Polarization Enhanced Light (mPEL) imaging. A target tissue can be Illuminated with light of defined polarization at a plurality of wavelengths or wavelength bands. Scattered light from the tissue is collected and its polarization states analyzed and detected either via a polarization sensitive camera or a combination or polarizing filters and a standard camera. Light detected at distinct polarization states and colors is weighted by a factor and combined to yield an image that results in optimized visualization of lesions and/or discrimination of malignant from benign lesions. The factors may be identified based on a combination of Monte Carlo simulations and regression analysis to yield enhanced sensitivity to the tissue scattering power. Alternatively, the factors may be identified through machine learning based optimization algorithms to optimize tissue classification.

Abstract: Methods and apparatus for improved imaging of internal tissue structures, such as lesions in the peritoneum, are disclosed employing Differentially Polarized Light (DPL) imaging. The optical system can include a laparoscope having at least one optical illumination waveguide for directing illuminating radiation and an optical collection waveguide having an aperture for collecting and transmitting radiation backscattered from a tissue region to a detector. The system further can include a polarizer for polarizing the illuminating radiation and a second analyzing polarizer disposed in the optical return path, whereby backscattered radiation of differing polarizations can be passed to the detector. End cap assemblies are also disclosed that that can be fitted to conventional laparoscopes, e.g., by a threaded connection or the like, to facilitate DPL imaging by polarizing the illuminating light of the laparoscope. For example, the end cap can include a polarizing film within a stainless steel housing.