Time-domain near-infrared spectroscopy (TD-NIRs) and Time-Domain Diffuse Correlation Spectroscopy (TD-DCS) are emerging imaging techniques that use a near-infrared, long coherence, pulsed laser to characterize oxygenation levels and blood flow. TD-DCS is a promising tool for bedside monitoring of brain activity due to its high time-resolution and portability. One potential new application area for TD-DCS is for detecting non-compressible torso hemorrhages (NCTH). NCTH is a serious traumatic injury that requires surgical intervention and is a leading cause of death in the military due to the lack of a rapid and portable imaging system sensitive enough to detect injury. Applying long wavelengths (1064 nm and 1120 nm) and time gating, TD-DCS can penetrate the superficial tissue layers and potentially detect bleeding deep within an organ. One limitation of current time-gating system is its reliance on full knowledge of the target tissue layers and properties in order to apply gating effectively. An automatic gating scheme that can adjust the time gate to quickly recalibrate itself to different imaging conditions, such as a different body area, can eliminate this limitation. Here, we use modeling and Monte Carlo simulations to search for characteristics in return signal profiles, specifically the time-of-flight and intensity profiles, as first step toward an automatic time-gating algorithm. We detail the simulation setups, parameter sweeps, and preliminary results in this report. These results show promise for TD-DCS as a tool for rapid and continuous monitoring of injuries in the field.
Our team has recently shown the SNR and depth-sensitivity advantages of using 1064 nm light for diffuse correlation spectroscopy as well as the challenges of commercially available single-photon detectors at this wavelength. We will review two strategies for custom readout integrated circuit designs that simultaneously target lower pixel dead times and lower afterpulsing probabilities. Both designs use macropixels comprising many detectors, each having a programmable hold-off time. We will compare simulated autocorrelations for our detector models and compare predicted performance against commercial InGaAs/InP detectors.
Smart pixel imaging with computational-imaging arrays (SPICA) transfers image plane coding typically realized in the optical architecture to the digital domain of the focal plane array, thereby minimizing signal-to-noise losses associated with static filters or apertures and inherent diffraction concerns. MIT Lincoln Laboratory has been developing digitalpixel focal plane array (DFPA) devices for many years. In this work, we leverage legacy designs modified with new features to realize a computational imaging array (CIA) with advanced pixel-processing capabilities. We briefly review the use of DFPAs for on-chip background removal and image plane filtering. We focus on two digital readout integrated circuits (DROICS) as CIAs for two-dimensional (2D) transient target tracking and three-dimensional (3D) transient target estimation using per-pixel coded-apertures or flutter shutters. This paper describes two DROICs – a SWIR pixelprocessing imager (SWIR-PPI) and a Visible CIA (VISCIA). SWIR-PPI is a DROIC with a 1 kHz global frame rate with a maximum per-pixel shuttering rate of 100 MHz, such that each pixel can be modulated by a time-varying, pseudorandom, and duo-binary signal (+1,-1,0). Combining per-pixel time-domain coding and processing enables 3D (x,y,t) target estimation with limited loss of spatial resolution. We evaluate structured and pseudo-random encoding strategies and employ linear inversion and non-linear inversion using total-variation minimization to estimate a 3D data cube from a single 2D temporally-encoded measurement. The VISCIA DROIC, while low-resolution, has a 6 kHz global frame rate and simultaneously encodes eight periodic or aperiodic transient target signatures at a maximum rate of 50 MHz using eight 8-bit counters. By transferring pixel-based image plane coding to the DROIC and utilizing sophisticated processing, our CIAs enable on-chip temporal super-resolution.