To address many of the deficiencies in optical neuroimaging technologies such as poor spatial resolution, time-consuming reconstruction, low penetration depth, and contact-based measurement, a novel, noncontact, time-resolved laser speckle contrast imaging (TR-LSCI) technique has been developed for continuous, fast, and high-resolution 2D mapping of cerebral blood flow (CBF) at different depths of the head. TR-LSCI illuminates the head with picosecond-pulsed, coherent, widefield near-infrared light and synchronizes a newly developed, high-resolution, gated single-photon avalanche diode camera (SwissSPAD2) to capture CBF maps at different depths. By selectively collecting diffuse photons with longer pathlengths through the head, TR-LSCI reduces partial volume artifacts from the overlying tissues, thus improving the accuracy of CBF measurement in the deep brain. CBF map reconstruction was dramatically expedited by incorporating highly parallelized computation. The performance of TR-LSCI was evaluated using head-simulating phantoms with known properties and in-vivo rodents with varied hemodynamic challenges to the brain. Results from these pilot studies demonstrated that TR-LSCI enabled mapping CBF variations at different depths with a sampling rate of up to 1 Hz and spatial resolutions ranging from tens of micrometers on the head surface to 1-2 millimeters in the deep brain. With additional improvements and validation in larger populations against established methods, we anticipate offering a noncontact, fast, high-resolution, portable, and affordable brain imager for fundamental neuroscience research in animals and for translational studies in humans.

Diffuse Correlation Spectroscopy (DCS) allows the label-free investigation of microvascular dynamics deep within living tissue. However, common implementations of DCS are currently limited to measurement depths of $\sim 1-1.5cm$, which can limit the accuracy of cerebral hemodynamics measurement. Here we present massively parallelized DCS (pDCS) using novel single photon avalanche detector (SPAD) arrays with up to 500x500 individual channels. The new SPAD array technology can boost the signal-to-noise ratio by a factor of up to 500 compared to single-pixel DCS, or by more than 15-fold compared to the most recent state-of-the-art pDCS demonstrations. Our results demonstrate the first in vivo use of this massively parallelized DCS system to measure cerebral blood flow changes at $\sim 2cm$ depth in human adults. We compared different modes of operation and applied a dual detection strategy, where a secondary SPAD array is used to simultaneously assess the superficial blood flow as a built-in reference measurement. While the blood flow in the superficial scalp tissue showed no significant change during cognitive activation, the deep pDCS measurement showed a statistically significant increase in the derived blood flow index of 8-12% when compared to the control rest state.

Continuous, noninvasive monitoring of cerebral blood flow (CBF) is vital for neurocritical care. Diffuse correlation spectroscopy (DCS) enables assessment of microvascular blood flow by analyzing speckle intensity fluctuations of near-infrared light. In this review, we summarize recent advances in TD-DCS using superconducting nanowire single-photon detectors (SNSPDs) at 1064 nm, as well as complementary developments in high-density CW-DCS systems using single-photon avalanche diode (SPAD) cameras. Time-gated photon detection improves depth sensitivity in TD-DCS, and the use of longer wavelengths provides advantages in tissue penetration, photon throughput, and safety margin under ANSI exposure limits. Clinically feasible SPAD-based implementations, while lacking time-of-flight resolution, enable large signal-to-noise ratio gains via massive pixel averaging and offer a room-temperature, scalable path to high-density optical tissue monitoring. Together, these developments highlight a growing set of technologies for clinical applications, including bedside brain monitoring in neurocritical care. We conclude with practical guidance on detector technologies, gating strategies, system packaging, and briefly discuss interferometric DCS and speckle contrast optical spectroscopy (SCOS) as synergistic extensions for high-resolution and high-coverage imaging.

The acquisition of the time of flight (ToF) of photons has found numerous applications in the biomedical field. Over the last decades, a few strategies have been proposed to deconvolve the temporal instrument response function (IRF) that distorts the experimental time-resolved data. However, these methods require burdensome computational strategies and regularization terms to mitigate noise contributions. Herein, we propose a deep learning model specifically to perform the deconvolution task in fluorescence lifetime imaging (FLI). The model is trained and validated with representative simulated FLI data with the goal of retrieving the true photon ToF distribution. Its performance and robustness are validated with well-controlled in vitro experiments using three time-resolved imaging modalities with markedly different temporal IRFs. The model aptitude is further established with in vivo preclinical investigation. Overall, these in vitro and in vivo validations demonstrate the flexibility and accuracy of deep learning model-based deconvolution in time-resolved FLI and diffuse optical imaging.

The SwissSPAD2/3 camera family is based on quarter megapixel single-photon avalanche diode (SPAD) time gated imagers. The 16.38-µm low-noise pixels feature a single-bit memory and built-in all-solid-state nanosecond time gating without the need for external image intensifiers. Microlenses have also been made available to increase the overall system sensitivity, including for high NA applications. SwissSPAD2/3 are coupled to FPGA platforms enabling a virtually noiseless streaming at up to 100 kpfs. A 1-bit accumulation of frames to reconfigurable number of bits was programmed on the FPGA for applications such as fluorescence lifetime imaging microscopy (FLIM). In other applications, a burst-mode read-out of 130,000 binary frames to a DDD3 memory of one sensor half was programmed on one FPGA for applications requiring full bitplanes. These initial configurations were extended to dual-FPGA systems capable of streaming data at near 100 kfps in continuous mode for long acquisition times. In such configuration one FPGA streams data from one sensor half to the other FPGA, which then sends the combined data stream to a host PC over PCIe at up to 3 GB/s. The eight PCIe lanes require careful design with differential routing and controlled impedance and the whole development presented significant hardware and firmware challenges. We also achieved full synchronization of two SwissSPAD2 camera systems over PCIe and characterized the pixel-to-pixel exposure timing alignment error to better than 150 ps with a time gate of 10 ns. The resulting platforms are unique enablers for quantum imaging applications, such as plenoptic maging, quantum LIDAR or quanta burst photography.

Significance:Fluorescence guidance is used clinically by surgeons to visualize anatomical and/or physiological phenomena in the surgical field that are difficult or impossible to detect by the naked eye. Such phenomena include tissue perfusion or molecular phenotypic information about the disease being resected. Conventional fluorescence-guided surgery relies on long, microsecond scale laser pulses to excite fluorescent probes. However, this technique only provides two-dimensional information; crucial depth information, such as the location of malignancy below the tissue surface, is not provided. Aim:We developed a depth sensing imaging technique using light detection and ranging (LiDAR) time-of-flight (TOF) technology to sense the depth of target tissue while overcoming the influence of tissue optical properties and fluorescent probe concentration. Approach:The technology is based on a large-format (512×512  pixel), binary, gated, single-photon avalanche diode (SPAD) sensor with an 18 ps time-gate step, synchronized with a picosecond pulsed laser. The fast response of the sensor was developed and tested for its ability to quantify fluorescent inclusions at depth and optical properties in tissue-like phantoms through analytical model fitting of the fast temporal remission data. Results:After calibration and algorithmic extraction of the data, the SPAD LiDAR technique allowed for sub-mm resolution depth sensing of fluorescent inclusions embedded in tissue-like phantoms, up to a maximum of 5 mm in depth. The approach provides robust depth sensing even in the presence of variable tissue optical properties and separates the effects of fluorescence depth from absorption and scattering variations. Conclusions:LiDAR TOF fluorescence imaging using an SPAD camera provides both fluorescence intensity images and the temporal profile of fluorescence, which can be used to determine the depth at which the signal is emitted over a wide field of view. The proposed tool enables fluorescence imaging at a higher depth in tissue and with higher spatial precision than standard, steady-state fluorescence imaging tools, such as intensity-based near-infrared fluorescence imaging, optical coherence tomography, Raman spectroscopy, or confocal microscopy. Integration of this technique into a standard surgical tool could enable rapid, more accurate estimation of resection boundaries, thereby improving the surgeon's efficacy and efficiency, and ultimately improving patient outcomes.

We report a deep RNN model for temporal point spread function (TPSFs) deconvolution in multimodal imaging systems to extract true sample fluorescence decay rate. It’s performance has been validated in phantom and well-plate data.

Correlation plenoptic imaging (CPI) is a novel technological imaging modality enabling to overcome drawbacks of standard plenoptic devices, while preserving their advantages. However, a major challenge in view of real-time application of CPI is related to the relevant amount of required frames and the consequent computational-intensive processing algorithm. In this work, we describe the design and implementation of an optimized processing algorithm that is portable to an efficient computational environment and exploits the highly parallel algorithm offered by GPUs. Improvements by a factor ranging from 20X, for correlation measurement, to 500X, for refocusing, are demonstrated. Exploration of the relation between the improvement in performance achieved and actual GPU capabilities also indicates the feasibility of near-real-time processing capability, opening up to the potential use of CPI for practical real-time application.

3D Fluorescence Molecular Tomography (FMT) is an important pre-clinical tool for quantifying and characterizing molecular markers for different diseases. Herein, we demonstrate, for the first time, 3D K-Space FMT reconstructions using a large time-gated SPAD camera, SwissSPAD2 (SS2). The 3D reconstruction results are obtained using traditional and Deep Neural Network-based inverse solvers. Moreover, the 3D reconstruction performance with SS2 is benchmarked against that obtained with a gated-ICCD camera. The reconstruction results obtained using SS2 are in good agreement with those obtained from the gated-ICCD.

SwissSPAD3 is the latest of a family of widefield time-gated SPAD imagers developed for fluorescence lifetime imaging (FLI) applications. Its distinctive features are (i) the ability to define shorter gates than its predecessors (width W < 1 ns), (ii) support for laser repetition rates up to at least 80 MHz and (iii) a dual-gate architecture providing an effective duty cycle of 100%. We present widefield macroscopic FLI measurements of short lifetime NIR dyes, analyzed using the phasor approach. The results are compared with those previously obtained with SwissSPAD2 and to theoretical predictions.

The overall sensitivity of frontside-illuminated, silicon single-photon avalanche diode (SPAD) arrays has often suffered from fill factor limitations. The fill factor loss can however be recovered by employing microlenses, whereby the challenges specific to SPAD arrays are represented by large pixel pitch (> 10 µm), low native fill factor (as low as ~10%), and large size (up to 10 mm). In this work we report on the implementation of refractive microlenses by means of photoresist masters, used to fabricate molds for imprints of UV curable hybrid polymers deposited on SPAD arrays. Replications were successfully carried out for the first time at wafer reticle level on different designs in the same technology and on single large SPAD arrays with very thin residual layers (~10 µm), as needed for better efficiency at higher numerical aperture (NA > 0.25). In general, concentration factors within 15-20% of the theoretical maximum were obtained for the smaller arrays achieving an effective fill factor of 75.6-83.2%. A concentration factor up to 4.2 was measured on large arrays with a pitch of 16.38 m and a native fill factor of 10.5%, whereas improved simulation tools could give a better estimate of the actual concentration factor. Spectral measurements were also carried out, resulting in good and uniform transmission in the visible and NIR.

Silicon-based single-photon avalanche diodes (SPADs) implemented in front-side illuminated arrays and imagers have often suffered from fill factor limitations. The corresponding reduced sensitivity can be sometimes traded off with longer acquisition times thanks to SPAD’s noiseless read-out. The use of SPADs can however be critically affected in many applications, especially when photon-starved, or when several photons need to be detected in coincidence. The fill factor loss can be recovered by employing microlens arrays, which are difficult to build with relatively large pitch (> 10 μm) and low native SPAD fill factor (as low as 10%). To address these challenges, we have developed several generations of refractive microlenses by photoresist reflow used to fabricate molds. These structures were used to imprint UV-curable hybrid polymer microlenses on SPAD arrays. Replications were successfully carried out on large SPAD arrays with very thin residual layers (~10 μm), as required for higher numerical aperture (NA > 0.25). Replications were also carried out for the first time in a multi-chip operation regime at the wafer reticle level. By optimizing the lens sag and residual layer thickness, concentration factors (CFs) within 15-20% of the theoretical maxima were obtained for the smaller arrays (32×32 and 512×1). The spectral response was flat above 400 nm. CF values up to 4.2 with good uniformity were measured on large 512×512 arrays with 16 μm pixel pitch and a native fill factor of 10.5%. This result was confirmed by simulations when using the actual measured lens shape. We thus demonstrated good spectral and spatial uniformity and high CF, while moving to higher NAs and larger sensor sizes with respect to previous work.

We report on LinoSPAD2, a single-photon camera system, comprising a 512×1 single-photon avalanche diode (SPAD) front-end and one or two FPGA-based back-ends. Digital signals generated by the SPADs are processed by the FPGA in real time, whereas the FPGA offers full reconfigurability at a very high level of granularity both in time and space domains. The LinoSPAD2 camera system can process 512 SPADs simultaneously through 256 channels, duplicated on each FPGA-based back-end, with a bank of 64 time-to-digital converters (TDCs) operating at 133 MSa/s, whereas each TDC has a time resolution of 20 ps (LSB). To the best of our knowledge, LinoSPAD2 is the first fully reconfigurable SPAD camera system of large format. The SPAD front-end features a pitch of 26.2 μ m, a native fill factor of 25.1%, and a microlens array achieving 2.3× concentration factor. At room temperature, the median dark count rate (DCR) is 80 cps at 7 V excess bias, the peak photon detection probability (PDP) is 53% at 520 nm wavelength, and the single-photon timing resolution (SPTR) is 50 ps FWHM. The instrument response function (IRF) is around 100 ps FWHM at system level. The LinoSPAD2 camera system is suitable for numerous applications, including LiDAR imaging, heralded spectroscopy, compressive Raman sensing, and other computational imaging techniques.

Diffuse correlation spectroscopy (DCS) is a promising noninvasive technique for monitoring cerebral blood flow and measuring cortex functional activation tasks. Taking multiple parallel measurements has been shown to increase sensitivity, but is not easily scalable with discrete optical detectors. Here we show that with a large 500 × 500 SPAD array and an advanced FPGA design, we achieve an SNR gain of almost 500 over single-pixel mDCS performance. The system can also be reconfigured to sacrifice SNR to decrease correlation bin width, with 400 ns resolution being demonstrated over 8000 pixels.

The LinoSPAD2 camera combines a 512×1 linear single-photon avalanche diode (SPAD) array with an FPGA-based photon-counting and time-stamping platform, to create a reconfigurable sensing system capable of detecting single photons.The read-out is fully parallel, where each SPAD is connected to a different FPGA input.The hardware can be reconfigured to achieve different functionalities, such as photon counters, time-to-digital converter (TDC) arrays and histogramming units.Time stamping is performed by an array of 64 TDCs, with 20 ps resolution (LSB), serving 256 channels by means of 4:1 sharing.At sensor level, the pixel pitch is 26.2 µm with a fill factor of 25.1%.The median dark count rate of each SPAD at room temperature is below 100 cps at 6V excess bias, the single-photon timing resolution (SPTR) of each channel is 50 ps FWHM, and the peak photon detection probability reaches ~50% at 510 nm at the same excess bias.The fill factor can be increased by 2.3× by means of microlenses, with good spatial uniformity and flat spectral response above 400 nm.At system level, the average instrument response function (IRF) is 135 ps FWHM.The LinoSPAD2 camera enables a wide range of time-of-flight and time-resolved applications, including 3D imaging, fluorescence lifetime imaging microscopy (FLIM), heralded spectroscopy, and compressive Raman imaging, to name a few.Thanks to its features, LinoSPAD2 is a novel generation of reconfigurable single-photon image sensors capable of adapting their read-out and processing to match application-specific requirements, and combining SPAD arrays with advanced, massively-parallel computational functionalities.

Semiconductor nanocrystals feature multiply-excited states that display intriguing physics and significantly impact nanocrystal-based technologies. Fluorescence supplies a natural probe to investigate these states. Still, direct observation of multiexciton fluorescence has proved elusive to existing spectroscopy techniques. Heralded Spectroscopy is a new tool based on a breakthrough single-particle, single-photon, sub-nanosecond spectrometer that utilizes temporal photon correlations to isolate multiexciton emission. This proceedings paper introduces Heralded Spectroscopy and reviews some of the novel insights it uncovered into exciton–exciton interactions within single nanocrystals. These include weak exciton–exciton interactions and their correlation with quantum confinement, biexciton spectral diffusion, multiple biexciton species and biexciton emission polarization.

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing spatio-temporally correlated photons from either entangled or chaotic sources to address the main limitations of conventional light-field imaging, namely, the poor spatial resolution and the reduced change of perspective for 3D imaging. However, the application potential of high-resolution imaging modalities relying on photon correlations is limited, in practice, by the need to collect a large number of frames. This creates a gap, unacceptable for many relevant tasks, between the time performance of correlated-light imaging and that of traditional imaging methods. In this article, we address this issue by exploiting the photon number correlations intrinsic in chaotic light, combined with a cutting-edge ultrafast sensor made of a large array of single-photon avalanche diodes (SPADs). This combination of source and sensor is embedded within a novel single-lens CPI scheme enabling to acquire 10 volumetric images per second. Our results place correlated-photon imaging at a competitive edge and prove its potential in practical applications.

Since the introduction of the intensity interferometer by Hanbury Brown and Twiss in the '50s and its subsequent adaptations to quantum optic experiments, photon correlations have played a significant role in optical research. An emerging detector technology, SPAD arrays, presents new opportunities to scale these experiments and exploit photon correlations in new regimes. I will describe a new temporal-spectral photon correlation technique based on these detectors, single-particle heralded spectroscopy. I will present new insights into the photophysics of multiply-excited semiconductor quantum dots uncovered by this method, hitherto inaccessible to existing approaches.

Near-infrared (NIR) fluorescence lifetime imaging (FLI) provides a unique contrast mechanism to monitor biological parameters and molecular events in vivo. Single-photon avalanche diode (SPAD) cameras have been recently demonstrated in FLI microscopy (FLIM) applications, but their suitability for in vivo macroscopic FLI (MFLI) in deep tissues remains to be demonstrated. Herein, we report in vivo NIR MFLI measurement with SwissSPAD2, a large time-gated SPAD camera. We first benchmark its performance in well-controlled in vitro experiments, ranging from monitoring environmental effects on fluorescence lifetime, to quantifying Förster resonant energy transfer (FRET) between dyes. Next, we use it for in vivo studies of target-drug engagement in live and intact tumor xenografts using FRET. Information obtained with SwissSPAD2 was successfully compared to that obtained with a gated intensified charge-coupled device (ICCD) camera, using two different approaches. Our results demonstrate that SPAD cameras offer a powerful technology for in vivo preclinical applications in the NIR window.