Gpufit: An open-source toolkit for GPU-accelerated curve fitting

Edge-illumination spectral phase-contrast tomography

Following the rapid, but independent, diffusion of x-ray spectral and phase-contrast systems, this work demonstrates the first combination of spectral and phase-contrast computed tomography (CT) obtained by using the edge-illumination technique and a CdTe small-pixel (62μm) spectral detector. A theoretical model is introduced, starting from a standard attenuation-based spectral decomposition and leading to spectral phase-contrast material decomposition. Each step of the model is followed by quantification of accuracy and sensitivity on experimental data of a test phantom containing different solutions with known concentrations. An example of a micro CT application (20μm voxel size) on an iodine-perfusedex vivomurine model is reported. The work demonstrates that spectral-phase contrast combines the advantages of spectral imaging, i.e. high-Zmaterial discrimination capability, and phase-contrast imaging, i.e. soft tissue sensitivity, yielding simultaneously mass density maps of water, calcium, and iodine with an accuracy of 1.1%, 3.5%, and 1.9% (root mean square errors), respectively. Results also show a 9-fold increase in the signal-to-noise ratio of the water channel when compared to standard spectral decomposition. The application to the murine model revealed the potential of the technique in the simultaneous 3D visualization of soft tissue, bone, and vasculature. While being implemented by using a broad spectrum (pink beam) at a synchrotron radiation facility (Elettra, Trieste, Italy), the proposed experimental setup can be readily translated to compact laboratory systems including conventional x-ray tubes.

Edge illumination x-ray phase contrast simulations using the CAD-ASTRA toolbox

Edge illumination x-ray phase contrast imaging (XPCI) provides increased contrast for low absorbing materials compared to attenuation images and sheds light on the material microstructure through dark field contrast. To apply XPCI in areas such as non-destructive testing and inline inspection, where scanned samples are increasingly compared to simulated reference images, accurate and efficient simulation software is required. However, currently available simulators rely on expensive Monte Carlo techniques or wave-optics frameworks, resulting in long simulation times. Furthermore, these simulators are often not optimized to work with computer-aided design (CAD) models, a common and memory-efficient method to represent manufactured objects, hindering their integration in an inspection pipeline. In this work, we address these shortcomings by introducing an edge illumination XPCI simulation framework built upon the recently developed CAD-ASTRA toolbox. CAD-ASTRA allows for the efficient simulation of x-ray projections from CAD models through GPU-accelerated ray tracing and supports ray refraction in a geometric optics framework. The edge illumination implementation is validated and its performance is benchmarked against GATE, a state-of-the-art Monte Carlo simulator, revealing a simulation speed increase of up to three orders of magnitude, while maintaining high accuracy in the resulting images.

Pulsed stimulated Brillouin microscopy enables high-sensitivity mechanical imaging of live and fragile biological specimens

Brillouin microscopy is an emerging optical elastography technique capable of assessing mechanical properties of biological samples in a three-dimensional, all-optical and noncontact fashion. The typically weak Brillouin scattering signal can be substantially enhanced via a stimulated Brillouin scattering (SBS) process; however, current implementations require high pump powers, which prohibit applications to photosensitive or live imaging of biological samples. Here we present a pulsed SBS scheme that takes advantage of the nonlinearity of the pump-probe interaction. In particular, we show that the required pump laser power can be decreased ~20-fold without affecting the signal levels or spectral precision. We demonstrate the low phototoxicity and high specificity of our pulsed SBS approach by imaging, with subcellular detail, sensitive single cells, zebrafish larvae, mouse embryos and adult Caenorhabditis elegans. Furthermore, our method permits observing the mechanics of organoids and C. elegans embryos over time, opening up further possibilities for the field of mechanobiology.

GPU-enabled real-time optical frequency comb spectroscopy and a photonic readout

We describe a GPU-enabled approach for real-time optical frequency comb spectroscopy in which data is recorded, Fourier transformed, normalized, and fit at data rates up to 2.2 GB/s. As an initial demonstration we have applied this approach to rapidly interrogate the motion of an optomechanical accelerometer through the use of an electro-optic frequency comb. We note that this approach is readily amenable to both self-heterodyne and dual-comb spectrometers for molecular spectroscopy as well as a photonic readout where the approach's agility, speed, and simplicity are expected to enable future improvements and applications.

High-resolution line-scan Brillouin microscopy for live imaging of mechanical properties during embryo development

Brillouin microscopy can assess mechanical properties of biological samples in a three-dimensional (3D), all-optical and hence non-contact fashion, but its weak signals often lead to long imaging times and require an illumination dosage harmful for living organisms. Here, we present a high-resolution line-scanning Brillouin microscope for multiplexed and hence fast 3D imaging of dynamic biological processes with low phototoxicity. The improved background suppression and resolution, in combination with fluorescence light-sheet imaging, enables the visualization of the mechanical properties of cells and tissues over space and time in living organism models such as fruit flies, ascidians and mouse embryos.

PEPI Lab: a flexible compact multi-modal setup for X-ray phase-contrast and spectral imaging

This paper presents a new flexible compact multi-modal imaging setup referred to as PEPI (Photon-counting Edge-illumination Phase-contrast imaging) Lab, which is based on the edge-illumination (EI) technique and a chromatic detector. The system enables both X-ray phase-contrast (XPCI) and spectral (XSI) imaging of samples on the centimeter scale. This work conceptually follows all the stages in its realization, from the design to the first imaging results. The setup can be operated in four different modes, i.e. photon-counting/conventional, spectral, double-mask EI, and single-mask EI, whereby the switch to any modality is fast, software controlled, and does not require any hardware modification or lengthy re-alignment procedures. The system specifications, ranging from the X-ray tube features to the mask material and aspect ratio, have been quantitatively studied and optimized through a dedicated Geant4 simulation platform, guiding the choice of the instrumentation. The realization of the imaging setup, both in terms of hardware and control software, is detailed and discussed with a focus on practical/experimental aspects. Flexibility and compactness (66 cm source-to-detector distance in EI) are ensured by dedicated motion stages, whereas spectral capabilities are enabled by the Pixirad-1/Pixie-III detector in combination with a tungsten anode X-ray source operating in the range 40-100 kVp. The stability of the system, when operated in EI, has been verified, and drifts leading to mask misalignment of less than 1 [Formula: see text]m have been measured over a period of 54 h. The first imaging results, one for each modality, demonstrate that the system fulfills its design requirements. Specifically, XSI tomographic images of an iodine-based phantom demonstrate the system's quantitativeness and sensibility to concentrations in the order of a few mg/ml. Planar XPCI images of a carpenter bee specimen, both in single and double-mask modes, demonstrate that refraction sensitivity (below 0.6 [Formula: see text]rad in double-mask mode) is comparable with other XPCI systems based on microfocus sources. Phase CT capabilities have also been tested on a dedicated plastic phantom, where the phase channel yielded a 15-fold higher signal-to-noise ratio with respect to attenuation.

An open-source microscopy framework for simultaneous control of image acquisition, reconstruction, and analysis

We present a computational framework to simultaneously perform image acquisition, reconstruction, and analysis in the context of open-source microscopy automation. The setup features multiple computer units intersecting software with hardware devices and achieves automation using python scripts. In practice, script files are executed in the acquisition computer and can perform any experiment by modifying the state of the hardware devices and accessing experimental data. The presented framework achieves concurrency by using multiple instances of ImSwitch and napari working simultaneously. ImSwitch is a flexible and modular open-source software package for microscope control, and napari is a multidimensional image viewer for scientific image analysis. The presented framework implements a system based on file watching, where multiple units monitor a filesystem that acts as the synchronization primitive. The proposed solution is valid for any microscope setup, supporting various biological applications. The only necessary element is a shared filesystem, common in any standard laboratory, even in resource-constrained settings. The file watcher functionality in Python can be easily integrated into other python-based software. We demonstrate the proposed solution by performing tiling experiments using the molecular nanoscale live imaging with sectioning ability (MoNaLISA) microscope, a high-throughput super-resolution microscope based on reversible saturable optical fluorescence transitions (RESOLFT).

Deep learning-assisted co-registration of full-spectral autofluorescence lifetime microscopic images with H&E-stained histology images

Autofluorescence lifetime images reveal unique characteristics of endogenous fluorescence in biological samples. Comprehensive understanding and clinical diagnosis rely on co-registration with the gold standard, histology images, which is extremely challenging due to the difference of both images. Here, we show an unsupervised image-to-image translation network that significantly improves the success of the co-registration using a conventional optimisation-based regression network, applicable to autofluorescence lifetime images at different emission wavelengths. A preliminary blind comparison by experienced researchers shows the superiority of our method on co-registration. The results also indicate that the approach is applicable to various image formats, like fluorescence in-tensity images. With the registration, stitching outcomes illustrate the distinct differences of the spectral lifetime across an unstained tissue, enabling macro-level rapid visual identification of lung cancer and cellular-level characterisation of cell variants and common types. The approach could be effortlessly extended to lifetime images beyond this range and other staining technologies.

Optimal precision and accuracy in 4Pi-STORM using dynamic spline PSF models

Coherent fluorescence imaging with two objective lenses (4Pi detection) enables single-molecule localization microscopy with sub-10 nm spatial resolution in three dimensions. Despite its outstanding sensitivity, wider application of this technique has been hindered by complex instrumentation and the challenging nature of the data analysis. Here we report the development of a 4Pi-STORM microscope, which obtains optimal resolution and accuracy by modeling the 4Pi point spread function (PSF) dynamically while also using a simpler optical design. Dynamic spline PSF models incorporate fluctuations in the modulation phase of the experimentally determined PSF, capturing the temporal evolution of the optical system. Our method reaches the theoretical limits for precision and minimizes phase-wrapping artifacts by making full use of the information content of the data. 4Pi-STORM achieves a near-isotropic three-dimensional localization precision of 2–3 nm, and we demonstrate its capabilities by investigating protein and nucleic acid organization in primary neurons and mammalian mitochondria.

A dynamic model of the 4Pi point spread function enables localization microscopy with exceptional three-dimensional resolution and a simpler optical design. 4Pi-STORM images of neurons and mitochondria reveal new details of nanoscale protein and nucleic acid organization.

Time-modulated excitation for enhanced single-molecule localization microscopy

Structured illumination in single-molecule localization microscopy provides new information on the position of molecules and thus improves the localization precision compared to standard localization methods. Here, we used a time-shifted sinusoidal excitation pattern to modulate the fluorescence signal of the molecules whose position information is carried by the phase and recovered by synchronous demodulation. We designed two flexible fast demodulation systems located upstream of the camera, allowing us to overcome the limiting camera acquisition frequency and thus to maximize the collection of photons in the demodulation process. The temporally modulated fluorescence signal was then sampled synchronously on the same image, repeatedly during acquisition. This microscopy, called ModLoc, allows us to experimentally improve the localization precision by a factor of 2.4 in one direction, compared to classical Gaussian fitting methods. A temporal study and an experimental demonstration both show that the short lifetimes of the molecules in blinking regimes impose a modulation frequency in the kilohertz range, which is beyond the reach of current cameras. A demodulation system operating at these frequencies would thus be necessary to take full advantage of this new localization approach.

This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Immunomagnetic microscopy of tumor tissues using quantum sensors in diamond

Histological imaging is essential for the biomedical research and clinical diagnosis of human cancer. Although optical microscopy provides a standard method, it is a persistent goal to develop new imaging methods for more precise histological examination. Here, we use nitrogen-vacancy centers in diamond as quantum sensors and demonstrate micrometer-resolution immunomagnetic microscopy (IMM) for human tumor tissues. We immunomagnetically labeled cancer biomarkers in tumor tissues with magnetic nanoparticles and imaged them in a 400-nm resolution diamond-based magnetic microscope. There is barely magnetic background in tissues, and the IMM can resist the impact of a light background. The distribution of biomarkers in the high-contrast magnetic images was reconstructed as that of the magnetic moment of magnetic nanoparticles by employing deep-learning algorithms. In the reconstructed magnetic images, the expression intensity of the biomarkers was quantified with the absolute magnetic signal. The IMM has excellent signal stability, and the magnetic signal in our samples had not changed after more than 1.5 y under ambient conditions. Furthermore, we realized multimodal imaging of tumor tissues by combining IMM with hematoxylin-eosin staining, immunohistochemistry, or immunofluorescence microscopy in the same tissue section. Overall, our study provides a different histological method for both molecular mechanism research and accurate diagnosis of human cancer.

Full spectrum fluorescence lifetime imaging with 0.5 nm spectral and 50 ps temporal resolution

The use of optical techniques to interrogate wide ranging samples from semiconductors to biological tissue for rapid analysis and diagnostics has gained wide adoption over the past decades. The desire to collect ever more spatially, spectrally and temporally detailed optical signatures for sample characterization has specifically driven a sharp rise in new optical microscopy technologies. Here we present a high-speed optical scanning microscope capable of capturing time resolved images across 512 spectral and 32 time channels in a single acquisition with the potential for ~0.2 frames per second (256 × 256 image pixels). Each pixel in the resulting images contains a detailed data cube for the study of diverse time resolved light driven phenomena. This is enabled by integration of system control electronics and on-chip processing which overcomes the challenges presented by high data volume and low imaging speed, often bottlenecks in previous systems.

High data volumes from multidimensional imaging techniques can lead to slow collection and processing times. Here, the authors implement multispectral fluorescence lifetime imaging microscopy (FLIM) that uses time-correlated photon counting technology to reach simultaneously high imaging rates combined with high spectral and temporal resolution.

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks

Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can be tested by means of targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the one hand, detailed mechanistic models can involve hundreds or thousands of molecular species and their intermediate complexes, as well as hundreds or thousands of chemical reactions, a situation generally occurring in rule-based modeling. On the other hand, the computational analysis of a model typically requires the execution of a large number of simulations for its calibration, or to test the effect of perturbations. As a consequence, the computational capabilities of modern Central Processing Units can be easily overtaken, possibly making the modeling of biochemical networks a worthless or ineffective effort. To the aim of overcoming the limitations of the current state-of-the-art simulation approaches, we present in this paper FiCoS, a novel "black-box" deterministic simulator that effectively realizes both a fine-grained and a coarse-grained parallelization on Graphics Processing Units. In particular, FiCoS exploits two different integration methods, namely, the Dormand-Prince and the Radau IIA, to efficiently solve both non-stiff and stiff systems of coupled Ordinary Differential Equations. We tested the performance of FiCoS against different deterministic simulators, by considering models of increasing size and by running analyses with increasing computational demands. FiCoS was able to dramatically speedup the computations up to 855×, showing to be a promising solution for the simulation and analysis of large-scale models of complex biological processes.

Low activity [11C]raclopride kinetic modeling in the mouse brain using the spatiotemporal kernel method

Depending on the molar activity of the tracer, the maximal allowable injected activity in mouse brain PET studies can be extremely low in order to avoid receptor saturation. Therefore, a high level of noise can be present in the image. We investigate several dynamic PET reconstruction methods in reduced counts, or equivalently in reduced injected activity, data exemplified in [¹¹C]racloprideBP_NDandR1quantification using the simplified reference tissue model (SRTM). We compared independent frame reconstruction (IFR), post-reconstruction HYPR denoising (IFR + HYPR), direct reconstruction using the SRTM model (DIR-SRTM), and the spatial (KERS) and spatiotemporal kernel reconstruction (KERST). Additionally, HYPR denoising of the frames used as features for the calculation of the spatial kernel matrix, was investigated (KERS-HYPR and KERST-HYPR).In vivodata of 11 mice, was used to generate list-mode data for five reduced count levels corresponding to reductions by a factor 4, 8, 12, 16 and 32 (equivalently 2.07, 1.04, 0.691, 0.518, and 0.260 MBq). Correlation of regionalBP_NDandR1values (reduced versus full counts reconstructions) was high (r > 0.94) for all methods, with KERS-HYPR and KERST-HYPR reaching the highest correlation (r > 0.96). Among methods with regularization, DIR-SRTM showed the largest variability inBP_ND(Bland-Altman SD from 3.0% to 12%), while IFR showed it forR1(5.1%-14.6%). KERST and KERST-HYPR were the only methods with Bland-Altman bias and SD below 5% for noise level up to a reduction factor of 16. At the voxel level,BP_NDandR1correlation was gradually decreased with increasing noise, with the largest correlation (BP_NDr > 0.88,R1r > 0.62) for KERS-HYPR and KERST-HYPR. The spatial and the spatiotemporal kernel methods performed similarly, while using only temporal regularization with direct reconstruction showed more variability. AlthoughR1 values present noise, using the spatiotemporal kernel reconstruction, accurate estimates of binding potential could be obtained with mouse injected activities as low as 0.26-0.518 MBq. This is desirable in order to maintain the tracer kinetics principle in mouse studies.

Molecular-scale axial localization by repetitive optical selective exposure

We introduce an axial localization with repetitive optical selective exposure (ROSE-Z) method for super-resolution imaging. By using an asymmetric optical scheme to generate interference fringes, a <2 nm axial localization precision was achieved with only ~3,000 photons, which is an approximately sixfold improvement compared to previous astigmatism methods. Nanoscale three-dimensional and two-color imaging was demonstrated, illustrating how this method achieves superior performance and facilitates the investigation of cellular nanostructures.

Computationally-efficient spatiotemporal correlation analysis super-resolves anomalous diffusion

Anomalous diffusion dynamics in confined nanoenvironments govern the macroscale properties and interactions of many biophysical and material systems. Currently, it is difficult to quantitatively link the nanoscale structure of porous media to anomalous diffusion within them. Fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) has been shown to extract nanoscale structure and Brownian diffusion dynamics within gels, liquid crystals, and polymers, but has limitations which hinder its wider application to more diverse, biophysically-relevant datasets. Here, we parallelize the least-squares curve fitting step on a GPU improving computation times by up to a factor of 40, implement anomalous diffusion and two-component Brownian diffusion models, and make fcsSOFI more accessible by packaging it in a user-friendly GUI. We apply fcsSOFI to simulations of the protein fibrinogen diffusing in polyacrylamide of varying matrix densities and super-resolve locations where slower, anomalous diffusion occurs within smaller, confined pores. The improvements to fcsSOFI in speed, scope, and usability will allow for the wider adoption of super-resolution correlation analysis to diverse research topics.

Fluorescence lifetime imaging with a megapixel SPAD camera and neural network lifetime estimation

Fluorescence lifetime imaging microscopy (FLIM) is a key technology that provides direct insight into cell metabolism, cell dynamics and protein activity. However, determining the lifetimes of different fluorescent proteins requires the detection of a relatively large number of photons, hence slowing down total acquisition times. Moreover, there are many cases, for example in studies of cell collectives, where wide-field imaging is desired. We report scan-less wide-field FLIM based on a 0.5 MP resolution, time-gated Single Photon Avalanche Diode (SPAD) camera, with acquisition rates up to 1 Hz. Fluorescence lifetime estimation is performed via a pre-trained artificial neural network with 1000-fold improvement in processing times compared to standard least squares fitting techniques. We utilised our system to image HT1080-human fibrosarcoma cell line as well as Convallaria. The results show promise for real-time FLIM and a viable route towards multi-megapixel fluorescence lifetime images, with a proof-of-principle mosaic image shown with 3.6 MP.

Evaluation of the ITER Real-Time Framework for Data Acquisition and Processing from Pulsed Gigasample Digitizers

Plasma diagnostics systems are becoming progressively more advanced. Contemporarily, researchers strive to achieve longer plasma pulses, and therefore, appropriate hardware is required. Analogue-to-Digital Converters are applied for data acquisition in many plasma diagnostic systems. Some diagnostic systems need data acquisition with gigahertz sampling frequency. However, gigasample digitizers working in continuous mode generate an enormous stream of data that requires suitable, high-performance processing systems. This becomes even more complicated and expensive for complex multi-channel systems. Nonetheless, numerous plasma diagnostic systems operate in a pulse mode. Thomson scattering (TS) diagnostics is a good example of a multi-channel system that does not require continuous data acquisition. Taking this into consideration, the authors decided to evaluate the CAEN DT5742 gigasample digitizer as a more cost-effective solution that would utilize the pulsed nature of the TS diagnostic system. The paper presents a complete data acquisition and processing system dedicated for plasma diagnostics based on the ITER real-time framework (RTF). Integration of RTF with real hardware is discussed. The authors of the paper have developed software including RTF function block for the CAEN DT5742 digitizer, example data processing algorithms, data archiving and publishing for plasma control system.

Toward Noninvasive Mapping of Diffuse Scattering in the Presence of Motion

Ultrasonic coda wave analysis techniques localize defects in fields such as seismography and nondestructive testing. In medical ultrasound, these techniques might provide novel mapping of tissue properties in diseases characterized by local fibrosis. In this work, we present an approach for localizing variation in scattering properties in the diffuse regime with an array transducer in medical ultrasound. This approach estimates coda wave decorrelation as the array is displaced by 0.5 mm, allowing data acquisition at two slightly different spatial locations. An inverse problem is solved as in nondestructive testing based on coda wave decorrelation estimates and a locally-estimated diffusion constant. The developed approach is demonstrated in a tissue-mimicking phantom to assess sensitivity to variation in scattering properties. Next, the ability of the approach for localizing regions of increased multiple scattering in biological tissues is assessed with a large multiple scattering bead in an ex vivo porcine cardiac sample. Through these experiments, the ability to map variation in multiple scattering is demonstrated for the first time, with a mean localization error of 1.42 ± 3.5 mm for this low-resolution mapping technique. While the goal of this technique is to map defects in the diffuse regime rather than to develop a conventional image, contrast ratios in the resulting images were in good agreement with scattering concentrations in phantom studies: 1.98 ± 0.05 for a 2× scattering target, 1.37 ± 0.02 for a 1.4× scattering target, 0.65 ± 0.02 for a 0.7× scattering target, and 0.49 ± 0.03 for a 0.5× scattering targets.

T2 and T2∗ mapping in ex situ porcine myocardium: myocardial intravariability, temporal stability and the effects of complete coronary occlusion

Diagnosis of ischaemia-related sudden cardiac death in the absence of microscopic and macroscopic ischaemic lesions remains a challenge for medical examiners. Medical imaging techniques increasingly provide support in post-mortem examinations by detecting and documenting internal findings prior to autopsy. Previous studies have characterised MR relaxation times to investigate post-mortem signs of myocardial infarction in forensic cohorts. In this prospective study based on an ex situ porcine heart model, we report fundamental findings related to intramyocardial variability and temporal stability of T₂ as well as the effects of permanent coronary occlusion on T₂ and T₂^∗ relaxation in post-mortem myocardium. The ex situ porcine hearts included in this study (n= 19) were examined in two groups (S_s, n= 11 and S_i, n= 8). All magnetic resonance imaging (MRI) examinations were performed ex situ, at room temperature and at 3 T. In the S_s group, T₂ mapping was performed on slaughterhouse porcine hearts at different post-mortem intervals (PMI) between 7 and 26 h. Regarding the intramyocardial variability, no statistically significant differences in T₂ were observed between myocardial segments (p= 0.167). Assessment of temporal stability indicated a weak negative correlation (r=- 0.21) between myocardial T₂ and PMI. In the S_i group, animals underwent ethanol-induced complete occlusion of the left anterior descending artery. T₂ and T₂^∗ mapping were performed within 3 h of death. Differences between the expected ischaemic and remote regions were statistically significant for T₂ (p= 0.007), however not for T₂^∗ (p= 0.062). Our results provide important information for future assessment of the diagnostic potential of quantitative MRI in the post-mortem detection of early acute myocardial infarction.

About samples, giving examples: Optimized Single Molecule Localization Microscopy

Super-resolution microscopy has profoundly transformed how we study the architecture of cells, revealing unknown structures and refining our view of cellular assemblies. Among the various techniques, the resolution of Single Molecule Localization Microscopy (SMLM) can reach the size of macromolecular complexes and offer key insights on their nanoscale arrangement in situ. SMLM is thus a demanding technique and taking advantage of its full potential requires specifically optimized procedures. Here we describe how we perform the successive steps of an SMLM workflow, focusing on single-color Stochastic Optical Reconstruction Microscopy (STORM) as well as multicolor DNA Points Accumulation for imaging in Nanoscale Topography (DNA-PAINT) of fixed samples. We provide detailed procedures for careful sample fixation and immunostaining of typical cellular structures: cytoskeleton, clathrin-coated pits, and organelles. We then offer guidelines for optimal imaging and processing of SMLM data in order to optimize reconstruction quality and avoid the generation of artifacts. We hope that the tips and tricks we discovered over the years and detail here will be useful for researchers looking to make the best possible SMLM images, a pre-requisite for meaningful biological discovery.

Portable hyperspectral lidar utilizing 5 GHz multichannel full waveform digitization

The Finnish Geospatial Research Institute hyperspectral LiDAR (FGI HSL) was one of the first multichannel terrestrial LiDARs capable of producing simultaneous 3-dimensional topography with spectral data. Supercontinuum-based HSL instruments developed so far have suffered from portability and sensitivity issues, severely restricting potential applications. Recently, we have implemented a new robust field design of the FGI HSL together with an improved pulse digitizing scheme. Small size and significantly improved measuring accuracy of this new system enable a range of novel applications that so far have been impractical for multichannel terrestrial LiDARs. Particularly, this new design has enabled us to perform measurements in underground mines and detect minute spectral differences in various rock types. In this paper, we present the design of our new LiDAR and preliminary algorithms together with a brief performance assessment of the device. In addition, we provide example measurements of typical rock samples found in a ferrochrome mine.

Derivation of Fiber Orientations From Oblique Views Through Human Brain Sections in 3D-Polarized Light Imaging

3D-Polarized Light Imaging (3D-PLI) enables high-resolution three-dimensional mapping of the nerve fiber architecture in unstained histological brain sections based on the intrinsic birefringence of myelinated nerve fibers. The interpretation of the measured birefringent signals comes with conjointly measured information about the local fiber birefringence strength and the fiber orientation. In this study, we present a novel approach to disentangle both parameters from each other based on a weighted least squares routine (ROFL) applied to oblique polarimetric 3D-PLI measurements. This approach was compared to a previously described analytical method on simulated and experimental data obtained from a post mortem human brain. Analysis of the simulations revealed in case of ROFL a distinctly increased level of confidence to determine steep and flat fiber orientations with respect to the brain sectioning plane. Based on analysis of histological sections of a human brain dataset, it was demonstrated that ROFL provides a coherent characterization of cortical, subcortical, and white matter regions in terms of fiber orientation and birefringence strength, within and across sections. Oblique measurements combined with ROFL analysis opens up new ways to determine physical brain tissue properties by means of 3D-PLI microscopy.

Real-time 3D single-molecule localization using experimental point spread functions

We present a real-time fitter for 3D single-molecule localization microscopy using experimental point spread functions (PSFs) that achieves minimal uncertainty in 3D on any microscope and is compatible with any PSF engineering approach. We used this method to image cellular structures and attained unprecedented image quality for astigmatic PSFs. The fitter compensates for most optical aberrations and makes accurate 3D super-resolution microscopy broadly accessible, even on standard microscopes without dedicated 3D optics.