Deep Autoencoder for Combined Human Pose Estimation and body Model Upscaling

We present a method for simultaneously estimating 3D human pose and body shape from a sparse set of wide-baseline camera views. We train a symmetric convolutional autoencoder with a dual loss that enforces learning of a latent representation that encodes skeletal joint positions, and at the same time learns a deep representation of volumetric body shape. We harness the latter to up-scale input volumetric data by a factor of $4 \times$, whilst recovering a 3D estimate of joint positions with equal or greater accuracy than the state of the art. Inference runs in real-time (25 fps) and has the potential for passive human behaviour monitoring where there is a requirement for high fidelity estimation of human body shape and pose

CosMIC: a consistent metric for spike inference from calcium imaging

In recent years, the development of algorithms to detect neuronal spiking activity from two-photon calcium imaging data has received much attention. Meanwhile, few researchers have examined the metrics used to assess the similarity of detected spike trains with the ground truth. We highlight the limitations of the two most commonly used metrics, the spike train correlation and success rate, and propose an alternative, which we refer to as CosMIC. Rather than operating on the true and estimated spike trains directly, the proposed metric assesses the similarity of the pulse trains obtained from convolution of the spike trains with a smoothing pulse. The pulse width, which is derived from the statistics of the imaging data, reflects the temporal tolerance of the metric. The final metric score is the size of the commonalities of the pulse trains as a fraction of their average size. Viewed through the lens of set theory, CosMIC resembles a continuous Sørensen-Dice coefficient — an index commonly used to assess the similarity of discrete, presence/absence data. We demonstrate the ability of the proposed metric to discriminate the precision and recall of spike train estimates. Unlike the spike train correlation, which appears to reward overestimation, the proposed metric score is maximised when the correct number of spikes have been detected. Furthermore, we show that CosMIC is more sensitive to the temporal precision of estimates than the success rate

Nuclear accessibility of β-actin mRNA is measured by 3D single-molecule real-time tracking

Imaging single proteins or RNAs allows direct visualization of the inner workings of the cell. Typically, three-dimensional (3D) images are acquired by sequentially capturing a series of 2D sections. The time required to step through the sample often impedes imaging of large numbers of rapidly moving molecules. Here we applied multifocus microscopy (MFM) to instantaneously capture 3D single-molecule real-time images in live cells, visualizing cell nuclei at 10 volumes per second. We developed image analysis techniques to analyze messenger RNA (mRNA) diffusion in the entire volume of the nucleus. Combining MFM with precise registration between fluorescently labeled mRNA, nuclear pore complexes, and chromatin, we obtained globally optimal image alignment within 80-nm precision using transformation models. We show that {beta}-actin mRNAs freely access the entire nucleus and fewer than 60% of mRNAs are more than 0.5 {my}m away from a nuclear pore, and we do so for the first time accounting for spatial inhomogeneity of nuclear organization

Time and wavelength resolved spectroscopy of turbid media using light continuum generated in a crystal fiber

We report a novel system for time-resolved diffuse remission spectral measurements, based on short light continuum pulses generated in an index-guided crystal fiber, and a spectrometer-equipped streak camera. The system enables spectral recordings of absorption and reduced scattering coefficients of turbid media in the wavelength range 500 - 1200 nm with a spectral resolution of 5 nm and a temporal resolution of 30 ps. The optical properties are calculated by fitting the solution of the diffusion equation to the time-dispersion curve at each wavelength. Example measurements are presented from an apple, a finger and a pharmaceutical tablet. (C) 2004 Optical Society of America

Time-resolved NIR/Vis spectroscopy for analysis of solids: Pharmaceutical tablets

Time-resolved spectroscopy in the visible and near-infrared (NIR) regions was used in a feasibility study for analysis of solid pharmaceuticals. The objective of the experiments was to study the interaction of light with pharmaceutical solids and to investigate the usefulness of the method as an analytical toot for spectroscopic analysis. In these experiments, a pulsed Ti:sapphire laser and white light generation in water was utilized to form a pulsed light source in the visible/NIR region. The light was focused onto the surface of tablets, and the transmitted light was detected by a time-resolving streak camera. Two types of measurements were performed. First, a spectrometer was put in front of the streak camera for spectral resolution. Secondly, the signal originating from different locations of the sample was collected. Time-resolved and wavelength/spatially resolved data were generated and compared for a number of different samples. The most striking result from the experiments is that the typical optical path length through a 3.5-mm-thick tablet is about 20-25 cm. This indicates very strong multiple scattering in these samples. Monte Carlo simulations and comparison with experimental data support very high scattering coefficients on the order of 500 cm(-1). Furthermore, the data evaluation shows that photons with a particular propagation time through the sample contain a higher chemical contrast than other propagation times or than steady-state information. In conclusion, time-resolved NIR spectroscopy yields more information about solid pharmaceutical samples than conventional steady-state spectroscopy

Scatter correction of transmission near-infrared spectra by photon migration data: Quantitative analysis of solids

The scope of this work is a new methodology to correct conventional near-infrared (NIR) data for scattering effects. The technique aims at measuring the absorption coefficient of the samples rather than the total attenuation measured in conventional NIR spectroscopy. The main advantage of this is that the absorption coefficient is independent of the path length of the light inside the sample and therefore independent of the scattering effects. The method is based on time-resolved spectroscopy and modeling of light transport by diffusion theory. This provides an independent measure of the scattering properties of the samples and therefore of the path length of light. This yields a clear advantage over other preprocessing techniques, where scattering effects are estimated and corrected for by using the shape of the measured spectrum only. Partial least squares (PLS) calibration models show that, by using the proposed evaluation scheme, the predictive ability is improved by 50% as compared to a model based on conventional NIR data alone. The method also makes it possible to predict the concentration of active substance in samples with other physical properties than the samples included in the calibration model