KEYWORDS: Fluorescence lifetime imaging, Microscopes, Confocal microscopy, Luminescence, Live cell imaging, Surface plasmons, In vivo imaging, Single photon, Resonance energy transfer, Imaging systems
We report the development of a novel confocal line-scanning microscope capable of acquiring video-frame rate TCSPC-based FLIM. The system consists of a one-dimensional laser beam, which is optically conjugated to a 1024×16 single photon avalanche diode(SPAD) based line-imaging CMOS(1), with 23.78 μm pixel pitch at 49.31% fill factor. Incorporation of on-chip histogramming on the line-sensor facilitates the acquisition of up to 16.5 Giga-photon counts/s, enabling operation 66 times faster than our previously reported bespoke high speed FLIM platforms. We will demonstrate its use in live-cell imaging investigating the roles that PAK proteins play in regulation of cytoskeletal dynamics.
Precisely characterising and quantifying interactions between tumour cells and their environment to understand metastatic mechanisms requires a multi-dimensional, high-speed imaging system. To this end, we report on the development of a compressive full spectrum fluorescence lifetime microscope that exploits a novel SPAD line sensor and a DMD to enable monitoring of dynamic sub-cellular interactions. At no cost to its temporal performance, the hyperspectral nature of the system helps to improve unmixing and, crucially, can detect the small spectral changes in the emission of fluorescent probes and intrinsic fluorophores that can occur in complex environments.
KEYWORDS: Raman spectroscopy, Single photon avalanche diodes, Calcite, Fluorescence, Single walled carbon nanotubes, Signal to noise ratio, CMOS sensors, Medical research, Imaging spectroscopy, Diamond
Time-resolved Raman and fluorescence lifetime spectroscopy imaging yields new research insights with great potential in applications including biomedical diagnostics, carbon materials, and battery development. Single Photon Avalanche Diode (SPAD) arrays are ideal for such applications and we present to our knowledge the first time-resolved Raman images obtained with such sensors. Utilizing motorized and confocal scanning configurations we obtain near shot-noise limited performance, room temperature operation, millisecond spectral acquisition times, and simultaneous acquisition and discrimination of Raman and fluorescence with high spectral resolution and range. Detailed images and spectra from samples including calcite, diamond, and single-wall carbon nanotubes demonstrate the possibility of high-resolution time-resolved Raman and fluorescence imaging.
We propose a handheld single photon avalanche diode (SPAD) micro-camera probe for wide-field in-vivo fluorescence lifetime imaging (FLIm) applications. The presented probe includes a novel 3D stacked 1.4 mm × 1.4 mm SPAD array, an integrated excitation light source, and imaging optics. The spatial and temporal performance of the integrated system was characterised using a USAF test target and range of fluorescence lifetime beads.
Raman spectroscopy is a hugely informative tool with a plethora of applications from biomedicine to analytical chemistry. Potentially, the technique could improve liver transplantation success rates through investigating Raman signals associated with metabolic changes prior to transplant rejection. However, studying biological systems is challenging since background fluorescence dominates the weak Raman signal. Thus, there is a need to improve signal-to-noise and Raman-tofluorescence ratios and drive down spectral acquisition times. Pulsed lasers combined with time-resolving single photon avalanche diode (SPAD) detection systems have been shown to enhance Raman and fluorescence discrimination. We report significant advances in time-correlated single photon counting (TCSPC) Raman spectroscopy using a laser exhibiting up to 200 W peak power and 40 MHz repetition rates in combination with a 512 spectral channel, 16.5 gigaevent/s throughput SPAD histogramming line sensor. Using a diamond sample, we report 0.4 MHz Raman count rates, millisecond spectral acquisition times, and signal-to-noise ratios of over 200. We demonstrate simultaneous, singleexposure acquisition of Raman and fluorescence signals in sesame oil. Time-based Raman-fluorescence discrimination techniques are subject to fluorescence signal tail influences from previous pulses, and data obtained with laser periods of 25 ns and 50 ns are presented. We achieved optimised Raman-to-fluorescence ratios through adjustment of histogram bin positions in 63 ps increments. Achieving high count rates while discriminating fluorescence from Raman signals unlocks the potential of combined Raman/fluorescence lifetime spectroscopy for biomedical imaging applications.
Time-domain microfluidic fluorescence lifetime flow cytometry enables observation of fluorescence decay of particles or cells over time using time-correlated single photon counting (TCSPC). This method requires the fluorescence lifetime measured from a limited number of photons and in a short amount of time. In current implementations of the technique, the low throughput of state of the art detectors and lack of real-time statistical analysis of the current technology, the timedomain approaches are usually coupled with off-line analysis which impedes its use in flow cell sorting, tracking and capturing. In this work, we apply a 32×32 CMOS SPAD array (MegaFrame camera) for real-time imaging flow cytometry analysis. This technology is integrated into a 1024-beam multifocal fluorescence microscope and incorporating a microfluidic chip at the sample plane enables imaging of cell flow and identification. Furthermore, the 1.5% native pixel fill-factor of the MegaFrame camera is overcome using beamlet reprojection with <10 μW laser power at 490 nm for each beam. Novel hardware algorithms incorporating the center-of-mass method (CMM) with real-time background subtraction and division are implemented within the firmware, allowing lossless recording of TCSPC events at a 500 kHz frame rate with 1024 histogram bins at 52 ps time resolution. Live calculation of background compensated CMM-based fluorescence lifetime is realized at a user-defined frame rate (typically 0.001 ~ 27 kHz) for each SPAD pixel. The work in this paper considers the application of the SPAD array to confocal fluorescence lifetime imaging of multiple coincident particles flowing within a microfluidic channel. Compared to previous flow systems based on single-point detectors, the multi-beam flow system enables visualization, detection and categorization of multiple groups of cells or particles according to their fluorescence lifetime.
We demonstrate a 512 x 16 CMOS single photon avalanche diode (SPAD) line sensor with per-pixel on-chip histogramming for video rate spectral fluorescence lifetime imaging (sFLIM). On-chip histogramming provides 32-bin histograms per pixel with 11bit/bin dynamic range. In addition, bin widths in time can be programmed from 51.20 ps to 6.55 ns, providing a histogram range from 1.64 ns to 209.72 ns to suit a wide range of fluorescence decays. At the end of a user defined exposure time, the full histogram data (i.e. 32-bins/pixel and 512 pixels) is first transferred to a FPGA in 84.48 μs via 64 data I/O pads at a 33.33 MHz I/O rate. The sensor data is then binned into two user defined spectral bands to provide spectral separation between different fluorophores, before being transferred to a PC via a USB3 connection for further processing. Fluorescence lifetimes for each spectral band are then rapidly estimated in software by applying the Centre-of-Mass Method (CMM), providing two 128 x 128 size spectral lifetime images in 1.384 s (i.e. with a frame rate of 0.72 fps). The frame rate can be increased by reducing the number of bins, reaching a maximum frame rate when only 2 bins are used with the Rapid Lifetime Determination (RLD) algorithm. In this paper we study the lifetime accuracy vs frame rate trade-offs by varying the number of histogram bins while carefully adjusting the bin widths for maximum bin counts. We validate the results using a Rhodamine 110 and Rhodamine B mixture solution which we separate them spectrally by their fluorescence lifetimes.
We present an achromatic confocal laser scanning system capable of recording spectrally resolved fluorescence lifetime images (sFLIMs) at a rate of >8 frames per second (FPS) for a 128 x 128 image. This frame rate was achieved by optimizing the processing of lifetime calculations from previous results which demonstrated >4 FPS sFLIM imaging. The imaging system is achromatic for a spectral range of 400 - 900 nm, achieved by using reflective optics instead of a transmissive lens system, except for the primary objectives. Two excitation sources have been integrated into the system, 485 nm and 640 nm laser diodes with a pulse width of <70 ps and <90 ps respectively. Imaging is performed via a galvanometric mirror system which scans the laser beam over the sample with the ability to change the Field of View (FOV) on the fly. The collected fluorescence signal is focused into a multimode fiber via a second objective and recollimated onto a transmissive grating for spectral dispersion onto a novel complementary metal–oxide–semiconductor single photon avalanche diode (CMOS SPAD) line array sensor. This sensor can perform lifetime histogram generation on-chip and process over 16.5 Giga events/s enabling fast lifetime data acquisition. High speed sFLIM is demonstrated through imaging of convallaria majalis sections.
Single-Photon Avalanche Diode (SPAD) sensors are one of the detectors of choice in LIDAR applications, due to their high sensitivity and time resolution. Traditionally, single-point SPAD detectors have been used, necessitating optical scanning, and hence leading to slower acquisition times. However, recent advances in SPAD technology have yielded high pixel count imagers. In these sensors, high sensitivity is ensured by maximising the photo-sensitive area of the device, whilst time-resolved capability is offered by the time stamping of photon detections and/or a programmable timegate synced to the laser source. The resulting sensors show an exciting promise for LIDAR, especially in challenging, low-light, high-speed applications.
KEYWORDS: Fluorescence resonance energy transfer, Sensors, Luminescence, Single photon, Time resolved spectroscopy, CMOS sensors, Spectroscopy, Molecules, Molecular energy transfer, Time correlated photon counting
We demonstrate a new 512x16 single photon avalanche diode (SPAD) based line sensor with per-pixel TCSPC histogramming for time-resolved, time-zoomable, FRET spectroscopy. The line sensor can operate in single photon counting (SPC) mode as well as time-correlated single photon counting (TCSPC) and per-pixel histogramming modes. TCSPC has been the preferred method for fluorescence lifetime measurements due to its collection of full decays as a histogram of arrival times. However, TCSPC is slow due to only capturing one photon per exposure and large timestamp data transfer requirements for offline histogramming. On-chip histogramming improves the data rate by allowing multiple SPAD pulses (up to one pulse per laser period) to be processed in each exposure cycle, along with secondly reducing the I/O bottleneck as only the final histogram is transferred. This can enable 50x higher acquisition rates (up to 10 billion counts per second), along with time-zoomable histogramming operation from 1.6ns to 205ns with 50ps resolution. A broad spectral range can be interrogated with the sensor (450-900nm). Overall, these sensors provide a unique combination of light sensing capabilities for use in high speed, sensitive, optical instrumentation in the time/wavelength domain. We test the sensor performance by observation of fluorescence resonance energy transfer (FRET) between FAM and TAMRA and between EGFP and RFP FRET standards.
KEYWORDS: Sensors, Spectrometers, Signal to noise ratio, Luminescence, CMOS sensors, Single photon, Spectroscopy, Imaging spectroscopy, Interference (communication), Time resolved spectroscopy
Time-resolved spectroscopy in the presence of noise is challenging. We have developed a new 512 pixel line sensor with 16 single-photon-avalanche (SPAD) detectors per pixel and ultrafast in-pixel time-correlated single photon counting (TCSPC) histogramming for such applications. SPADs are near shot noise limited detectors but we are still faced with the problem of high dark count rate (DCR) SPADs. The noisiest SPADs can be switched off to optimise signal-to-noiseratios (SNR) at the expense of longer acquisition/exposure times than would be possible if more SPADs were exploited. Here we present detailed noise characterization of our array. We build a DCR map for the sensor and demonstrate the effect of switching off the noisiest SPADs in each pixel. 24% percent of SPADs in the array are measured to have DCR in excess of 1kHz, while the best SPAD selection per pixel reduces DCR to 53+/-7Hz across the entire array. We demonstrate that selection of the lowest DCR SPAD in each pixel leads to the emergence of sparse spatial sampling noise in the sensor.
The SPADnet FP7 European project is aimed at a new generation of fully digital, scalable and networked photonic components to enable large area image sensors, with primary target gamma-ray and coincidence detection in (Time-of- Flight) Positron Emission Tomography (PET). SPADnet relies on standard CMOS technology, therefore allowing for MRI compatibility. SPADnet innovates in several areas of PET systems, from optical coupling to single-photon sensor architectures, from intelligent ring networks to reconstruction algorithms. It is built around a natively digital, intelligent SPAD (Single-Photon Avalanche Diode)-based sensor device which comprises an array of 8×16 pixels, each composed of 4 mini-SiPMs with in situ time-to-digital conversion, a multi-ring network to filter, carry, and process data produced by the sensors at 2Gbps, and a 130nm CMOS process enabling mass-production of photonic modules that are optically interfaced to scintillator crystals. A few tens of sensor devices are tightly abutted on a single PCB to form a so-called sensor tile, thanks to TSV (Through Silicon Via) connections to their backside (replacing conventional wire bonding). The sensor tile is in turn interfaced to an FPGA-based PCB on its back. The resulting photonic module acts as an autonomous sensing and computing unit, individually detecting gamma photons as well as thermal and Compton events. It determines in real time basic information for each scintillation event, such as exact time of arrival, position and energy, and communicates it to its peers in the field of view. Coincidence detection does therefore occur directly in the ring itself, in a differed and distributed manner to ensure scalability. The selected true coincidence events are then collected by a snooper module, from which they are transferred to an external reconstruction computer using Gigabit Ethernet.
The rapid advancements in ad hoc sensor networks, MEMS (micro-electro-mechanical systems) devices, low-power
electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms,
distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance
satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may
have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different
levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive
approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms,
particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels.
The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from
the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the
proposed approach through its application in solving both node-level and system-level optimization problems.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.