Image-guided surgery can enhance cancer treatment by decreasing, and ideally eliminating, positive tumor margins and iatrogenic damage to healthy tissue. Current state-of-the-art near-infrared fluorescence imaging systems are bulky and costly, lack sensitivity under surgical illumination, and lack co-registration accuracy between multimodal images. As a result, an overwhelming majority of physicians still rely on their unaided eyes and palpation as the primary sensing modalities for distinguishing cancerous from healthy tissue. Here we introduce an innovative design, comprising an artificial multispectral sensor inspired by the Morpho butterfly’s compound eye, which can significantly improve image-guided surgery. By monolithically integrating spectral tapetal filters with photodetectors, we have realized a single-chip multispectral imager with 1000 × higher sensitivity and 7 × better spatial co-registration accuracy compared to clinical imaging systems in current use. Preclinical and clinical data demonstrate that this technology seamlessly integrates into the surgical workflow while providing surgeons with real-time information on the location of cancerous tissue and sentinel lymph nodes. Due to its low manufacturing cost, our bio-inspired sensor will provide resource-limited hospitals with much-needed technology to enable more accurate value-based health care.
The polarization properties of reflected light capture important information about the object's inherent properties: material composition, i.e. index of refraction and scattering properties, and shape of the object, i.e. surface normal. Polarization information therefore has been used for surface reconstruction using a single-view camera with unpolarized incident light. However, this surface normal reconstruction technique suffers from a zenith angle ambiguity. In this paper, we have utilized circularly polarized light to solve for the zenith ambiguity by developing a detailed model using Mueller matrix formulism and division of focal plane polarization imaging technology. Experiment results validate our model for accurate surface reconstruction.
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