We report an imaging sensor capable of recording the optical properties of partially polarized light by monolithically integrating aluminum nanowire optical filters with a CCD imaging array. The imaging sensor, composed of 1000 by 1000 imaging elements with 7.4 μm pixel pitch, is covered with an array of pixel-pitch matched nanowire optical filters with four different orientations offset by 45°. The polarization imaging sensor has a signal-to-noise ratio of 45 dB and captures intensity, angle and degree of linear polarization in the visible spectrum at 40 frames per second with 300 mW of power consumption.

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro–optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal–oxide–semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors.

These insights into native ligament microstructure can be used to assess graft options for ACL reconstruction and optimize surgical reconstruction techniques.

A technique for creating maps of the direction and strength of fiber alignment in collagenous soft tissues is presented. The method uses a division of focal plane polarimeter to measure circularly polarized light transmitted through the tissue. The architecture of the sensor allows measurement of the retardance and fiber alignment at the full frame rate of the sensor without any moving optics. The technique compares favorably to the standard method of using a rotating polarizer. How the new technique enables real-time capture of the full angular spread of fiber alignment and retardance under various cyclic loading conditions is illustrated.

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.