Robust Single-view Cone-beam X-ray Pose Estimation with Neural Tuned Tomography (NeTT) and Masked Neural Radiance Fields (mNeRF)

Many tasks performed in image-guided, mini-invasive, medical procedures can be cast as pose estimation problems, where an X-ray projection is utilized to reach a target in 3D space. Expanding on recent advances in the differentiable rendering of optically reflective materials, we introduce new methods for pose estimation of radiolucent objects using X-ray projections, and we demonstrate the critical role of optimal view synthesis in performing this task. We first develop an algorithm (DiffDRR) that efficiently computes Digitally Reconstructed Radiographs (DRRs) and leverages automatic differentiation within TensorFlow. Pose estimation is performed by iterative gradient descent using a loss function that quantifies the similarity of the DRR synthesized from a randomly initialized pose and the true fluoroscopic image at the target pose. We propose two novel methods for high-fidelity view synthesis, Neural Tuned Tomography (NeTT) and masked Neural Radiance Fields (mNeRF). Both methods rely on classic Cone-Beam Computerized Tomography (CBCT); NeTT directly optimizes the CBCT densities, while the non-zero values of mNeRF are constrained by a 3D mask of the anatomic region segmented from CBCT. We demonstrate that both NeTT and mNeRF distinctly improve pose estimation within our framework. By defining a successful pose estimate to be a 3D angle error of less than 3 deg, we find that NeTT and mNeRF can achieve similar results, both with overall success rates more than 93%. However, the computational cost of NeTT is significantly lower than mNeRF in both training and pose estimation. Furthermore, we show that a NeTT trained for a single subject can generalize to synthesize high-fidelity DRRs and ensure robust pose estimations for all other subjects. Therefore, we suggest that NeTT is an attractive option for robust pose estimation using fluoroscopic projections

Sources and characteristics of summertime organic aerosol in the Colorado Front Range: perspective from measurements and WRF-Chem modeling

Abstract. The evolution of organic aerosols (OAs) and their precursors in the boundary layer (BL) of the Colorado Front Range during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ, July–August 2014) was analyzed by in situ measurements and chemical transport modeling. Measurements indicated significant production of secondary OA (SOA), with enhancement ratio of OA with respect to carbon monoxide (CO) reaching 0.085±0.003 µg m−3 ppbv−1. At background mixing ratios of CO, up to  ∼  1.8 µg m−3 background OA was observed, suggesting significant non-combustion contribution to OA in the Front Range. The mean concentration of OA in plumes with a high influence of oil and natural gas (O&G) emissions was  ∼  40 % higher than in urban-influenced plumes. Positive matrix factorization (PMF) confirmed a dominant contribution of secondary, oxygenated OA (OOA) in the boundary layer instead of fresh, hydrocarbon-like OA (HOA). Combinations of primary OA (POA) volatility assumptions, aging of semi-volatile species, and different emission estimates from the O&G sector were used in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulation scenarios. The assumption of semi-volatile POA resulted in greater than a factor of 10 lower POA concentrations compared to PMF-resolved HOA. Including top-down modified O&G emissions resulted in substantially better agreements in modeled ethane, toluene, hydroxyl radical, and ozone compared to measurements in the high-O&G-influenced plumes. By including emissions from the O&G sector using the top-down approach, it was estimated that the O&G sector contributed to  <  5 % of total OA, but up to 38 % of anthropogenic SOA (aSOA) in the region. The best agreement between the measured and simulated median OA was achieved by limiting the extent of biogenic hydrocarbon aging and consequently biogenic SOA (bSOA) production. Despite a lower production of bSOA in this scenario, contribution of bSOA to total SOA remained high at 40–54 %. Future studies aiming at a better emissions characterization of POA and intermediate-volatility organic compounds (IVOCs) from the O&G sector are valuable

Ozone, aerosol, potential vorticity, and trace gas trends observed at high‐latitudes over North America from February to May 2000

Ozone (O3) and aerosol scattering ratio profiles were obtained from airborne lidar measurements on thirty‐eight flights over seven deployments covering the latitudes of 40°–85°N between 4 February and 23 May 2000 as part of the Tropospheric Ozone Production about the Spring Equinox (TOPSE) field experiment. Each deployment started from Broomfield, Colorado, with bases in Churchill, Canada, and on most deployments, Thule Air Base, Greenland. Nadir and zenith lidar O3 measurements were combined with in situ O3 measurements to produce vertically continuous O3 profiles from near the surface to above the tropopause. Potential vorticity (PV) distributions along the flight track were obtained from several different meteorological analyses. Ozone, aerosol, and PV distributions were used together to identify the presence of pollution plumes and stratospheric intrusions. Ozone was found to increase in the middle free troposphere (4–6 km) at high latitudes (60°–85°N) by an average of 4.6 ppbv/mo (parts per billion by volume per month) from about 54 ppbv in early February to over 72 ppbv in mid‐May. The average aerosol scattering ratios at 1064 nm in the same region increased rapidly at an average rate of 0.36/mo from about 0.38 to over 1.7. Ozone and aerosol scattering were highly correlated over the entire field experiment, and PV and beryllium (7Be) showed no significant positive trend over the same period. The primary cause of the observed O3 increase in the mid troposphere at high latitudes was determined to be the photochemical production of O3 in pollution plumes with less than 20% of the increase from stratospherically‐derived O3

Non-Centered Spike-Triggered Covariance Analysis Reveals Neurotrophin-3 as a Developmental Regulator of Receptive Field Properties of ON-OFF Retinal Ganglion Cells

The functional separation of ON and OFF pathways, one of the fundamental features of the visual system, starts in the retina. During postnatal development, some retinal ganglion cells (RGCs) whose dendrites arborize in both ON and OFF sublaminae of the inner plexiform layer transform into RGCs with dendrites that monostratify in either the ON or OFF sublamina, acquiring final dendritic morphology in a subtype-dependent manner. Little is known about how the receptive field (RF) properties of ON, OFF, and ON-OFF RGCs mature during this time because of the lack of a reliable and efficient method to classify RGCs into these subtypes. To address this deficiency, we developed an innovative variant of Spike Triggered Covariance (STC) analysis, which we term Spike Triggered Covariance – Non-Centered (STC-NC) analysis. Using a multi-electrode array (MEA), we recorded the responses of a large population of mouse RGCs to a Gaussian white noise stimulus. As expected, the Spike-Triggered Average (STA) fails to identify responses driven by symmetric static nonlinearities such as those that underlie ON-OFF center RGC behavior. The STC-NC technique, in contrast, provides an efficient means to identify ON-OFF responses and quantify their RF center sizes accurately. Using this new tool, we find that RGCs gradually develop sensitivity to focal stimulation after eye opening, that the percentage of ON-OFF center cells decreases with age, and that RF centers of ON and ON-OFF cells become smaller. Importantly, we demonstrate for the first time that neurotrophin-3 (NT-3) regulates the development of physiological properties of ON-OFF center RGCs. Overexpression of NT-3 leads to the precocious maturation of RGC responsiveness and accelerates the developmental decrease of RF center size in ON-OFF cells. In summary, our study introduces STC-NC analysis which successfully identifies subtype RGCs and demonstrates how RF development relates to a neurotrophic driver in the retina

Influence of Corn Residue Harvest Management on Grain, Stover, and Energy Yields

Economic, environmental, and energy independence issues are contributing to rising fossil fuel prices, petroleum supply concerns, and a growing interest in biomass feedstocks as renewable energy sources. Potential feedstocks include perennial grasses, timber, and annual grain crops with our focus being on corn (Zea mays L.) stover. A plot-scale study evaluating stover removal was initiated in 2008 on a South Carolina Coastal Plain Coxville/Rains–Goldsboro– Lynchburg soil association site. In addition to grain and stover yields, carbon balance, greenhouse gas (GHG) emissions and soil quality impact reported elsewhere in this issue, variation in gross energy distribution within various plant fractions — whole plant, below ear shank (bottom), above ear shank (top), cob, as well as leaves and stems of the bottomand top portions (n(part, year)=20) was measured with an isoperibol calorimeter. Stalks from above the ear shank were the most energy dense, averaging 18.8 MJ/kg db, and when combined with other plant parts from above the ear shank, the entire top half was more energy dense than the bottom half — 18.4 versus 18.2 MJ/kg db. Gross energy content of the whole plant, including the cob, averaged 18.28±0.76 MJ/kg db. Over the 4 years, partial to total removal (i.e., 25%to 100 %) of above ground plant biomass could supply between 30 and 168 GJ/ha depending upon annual rainfall. At 168 GJ/ha, the quantity of corn stover biomass (whole plant) available in a 3,254-km2 area (32 km radius) around the study site could potentially support a 500-MW power plant

Incorporation of the electrode-electrolyte interface into finite-element models of metal microelectrodes

An accurate description of the electrode-electrolyte interfacial impedance is critical to the development of computational models of neural recording and stimulation that aim to improve understanding of neuro-electric interfaces and to expedite electrode design. This work examines the effect that the electrode-electrolyte interfacial impedance has upon the solutions generated from time-harmonic finite-element models of cone- and disk-shaped platinum microelectrodes submerged in physiological saline. A thin-layer approximation is utilized to incorporate a platinum-saline interfacial impedance into the finite-element models. This approximation is easy to implement and is not computationally costly. Using an iterative nonlinear solver, solutions were obtained for systems in which the electrode was driven at ac potentials with amplitudes from 10 mV to 500 mV and frequencies from 100 Hz to 100 kHz. The results of these simulations indicate that, under certain conditions, incorporation of the interface may strongly affect the solutions obtained. This effect, however, is dependent upon the amplitude of the driving potential and, to a lesser extent, its frequency. The solutions are most strongly affected at low amplitudes where the impedance of the interface is large. Here, the current density distribution that is calculated from models incorporating the interface is much more uniform than the current density distribution generated by models that neglect the interface. At higher potential amplitudes, however, the impedance of the interface decreases, and its effect on the solutions obtained is attenuated