Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation

The limited ability of Convolutional Neural Networks to generalize to images from previously unseen domains is a major limitation, in particular, for safety-critical clinical tasks such as dermoscopic skin cancer classification. In order to translate CNN-based applications into the clinic, it is essential that they are able to adapt to domain shifts. Such new conditions can arise through the use of different image acquisition systems or varying lighting conditions. In dermoscopy, shifts can also occur as a change in patient age or occurence of rare lesion localizations (e.g. palms). These are not prominently represented in most training datasets and can therefore lead to a decrease in performance. In order to verify the generalizability of classification models in real world clinical settings it is crucial to have access to data which mimics such domain shifts. To our knowledge no dermoscopic image dataset exists where such domain shifts are properly described and quantified. We therefore grouped publicly available images from ISIC archive based on their metadata (e.g. acquisition location, lesion localization, patient age) to generate meaningful domains. To verify that these domains are in fact distinct, we used multiple quantification measures to estimate the presence and intensity of domain shifts. Additionally, we analyzed the performance on these domains with and without an unsupervised domain adaptation technique. We observed that in most of our grouped domains, domain shifts in fact exist. Based on our results, we believe these datasets to be helpful for testing the generalization capabilities of dermoscopic skin cancer classifiers

Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation

he limited ability of Convolutional Neural Networks to generalize to images from previously unseen domains is a major limitation, in particular, for safety-critical clinical tasks such as dermoscopic skin cancer classification. In order to translate CNN-based applications into the clinic, it is essential that they are able to adapt to domain shifts. Such new conditions can arise through the use of different image acquisition systems or varying lighting conditions. In dermoscopy, shifts can also occur as a change in patient age or occurrence of rare lesion localizations (e.g. palms). These are not prominently represented in most training datasets and can therefore lead to a decrease in performance. In order to verify the generalizability of classification models in real world clinical settings it is crucial to have access to data which mimics such domain shifts. To our knowledge no dermoscopic image dataset exists where such domain shifts are properly described and quantified. We therefore grouped publicly available images from ISIC archive based on their metadata (e.g. acquisition location, lesion localization, patient age) to generate meaningful domains. To verify that these domains are in fact distinct, we used multiple quantification measures to estimate the presence and intensity of domain shifts. Additionally, we analyzed the performance on these domains with and without an unsupervised domain adaptation technique. We observed that in most of our grouped domains, domain shifts in fact exist. Based on our results, we believe these datasets to be helpful for testing the generalization capabilities of dermoscopic skin cancer classifiers

Biological Denitrification of High Nitrate Processing Wastewaters from Explosives Production Plant

Wastewater samples originating from an explosives production plant (3,000 mg N l−1 nitrate, 4.8 mg l−1 nitroglycerin, 1.9 mg l−1 nitroglycol and 1,200 mg l−1 chemical oxygen demand) were subjected to biological purification. An attempt to completely remove nitrate and to decrease the chemical oxygen demand was carried out under anaerobic conditions. A soil isolated microbial consortium capable of biodegrading various organic compounds and reduce nitrate to atmospheric nitrogen under anaerobic conditions was used. Complete removal of nitrates with simultaneous elimination of nitroglycerin and ethylene glycol dinitrate (nitroglycol) was achieved as a result of the conducted research. Specific nitrate reduction rate was estimated at 12.3 mg N g−1 VSS h−1. Toxicity of wastewater samples during the denitrification process was studied by measuring the activity of dehydrogenases in the activated sludge. Mutagenicity was determined by employing the Ames test. The maximum mutagenic activity did not exceed 0.5. The obtained results suggest that the studied wastewater samples did not exhibit mutagenic properties

Ambient-noise tomography of the wider Vienna Basin region

We present a new 3-D shear-velocity model for the top 30 km of the crust in the wider Vienna Basin region based on surface waves extracted from ambient-noise cross-correlations. We use continuous seismic records of 63 broad-band stations of the AlpArray project to retrieve interstation Green’s functions from ambient-noise cross-correlations in the period range from 5 to 25 s. From these Green’s functions, we measure Rayleigh group traveltimes, utilizing all four components of the cross-correlation tensor, which are associated with Rayleigh waves (ZZ, RR, RZ and ZR), to exploit multiple measurements per station pair. A set of selection criteria is applied to ensure that we use high-quality recordings of fundamental Rayleigh modes. We regionalize the interstation group velocities in a 5 km × 5 km grid with an average path density of ∼20 paths per cell. From the resulting group-velocity maps, we extract local 1-D dispersion curves for each cell and invert all cells independently to retrieve the crustal shear-velocity structure of the study area. The resulting model provides a previously unachieved lateral resolution of seismic velocities in the region of ∼15 km. As major features, we image the Vienna Basin and Little Hungarian Plain as low-velocity anomalies, and the Bohemian Massif with high velocities. The edges of these features are marked with prominent velocity contrasts correlated with faults, such as the Alpine Front and Vienna Basin transfer fault system. The observed structures correlate well with surface geology, gravitational anomalies and the few known crystalline basement depths from boreholes. For depths larger than those reached by boreholes, the new model allows new insight into the complex structure of the Vienna Basin and surrounding areas, including deep low-velocity zones, which we image with previously unachieved detail. This model may be used in the future to interpret the deeper structures and tectonic evolution of the wider Vienna Basin region, evaluate natural resources, model wave propagation and improve earthquake locations, among others

Arrival angles of teleseismic fundamental mode Rayleigh waves across the AlpArray

The dense AlpArray network allows studying seismic wave propagation with high spatial resolution. Here we introduce an array approach to measure arrival angles of teleseismic Rayleigh waves. The approach combines the advantages of phase correlation as in the two-station method with array beamforming to obtain the phase-velocity vector. 20 earthquakes from the first two years of the AlpArray project are selected, and spatial patterns of arrival-angle deviations across the AlpArray are shown in maps, depending on period and earthquake location. The cause of these intriguing spatial patterns is discussed. A simple wave-propagation modelling example using an isolated anomaly and a Gaussian beam solution suggests that much of the complexity can be explained as a result of wave interference after passing a structural anomaly along the wave paths. This indicates that arrival-angle information constitutes useful additional information on the Earth structure, beyond what is currently used in inversions

Shear-wave velocity structure beneath the Dinarides from the inversion of Rayleigh-wave dispersion

Highlights • Rayleigh-wave phase velocity in the wider Dinarides region using the two-station method. • Uppermost mantle shear-wave velocity model of the Dinarides-Adriatic Sea region. • Velocity model reveals a robust high-velocity anomaly present under the whole Dinarides. • High-velocity anomaly reaches depth of 160 km in the northern Dinarides to more than 200 km under southern Dinarides. • New structural model incorporating delamination as one of the processes controlling the continental collision in the Dinarides. The interaction between the Adriatic microplate (Adria) and Eurasia is the main driving factor in the central Mediterranean tectonics. Their interplay has shaped the geodynamics of the whole region and formed several mountain belts including Alps, Dinarides and Apennines. Among these, Dinarides are the least investigated and little is known about the underlying geodynamic processes. There are numerous open questions about the current state of interaction between Adria and Eurasia under the Dinaric domain. One of the most interesting is the nature of lithospheric underthrusting of Adriatic plate, e.g. length of the slab or varying slab disposition along the orogen. Previous investigations have found a low-velocity zone in the uppermost mantle under the northern-central Dinarides which was interpreted as a slab gap. Conversely, several newer studies have indicated the presence of the continuous slab under the Dinarides with no trace of the low velocity zone. Thus, to investigate the Dinaric mantle structure further, we use regional-to-teleseismic surface-wave records from 98 seismic stations in the wider Dinarides region to create a 3D shear-wave velocity model. More precisely, a two-station method is used to extract Rayleigh-wave phase velocity while tomography and 1D inversion of the phase velocity are employed to map the depth dependent shear-wave velocity. Resulting velocity model reveals a robust high-velocity anomaly present under the whole Dinarides, reaching the depths of 160 km in the north to more than 200 km under southern Dinarides. These results do not agree with most of the previous investigations and show continuous underthrusting of the Adriatic lithosphere under Europe along the whole Dinaric region. The geometry of the down-going slab varies from the deeper slab in the north and south to the shallower underthrusting in the center. On-top of both north and south slabs there is a low-velocity wedge indicating lithospheric delamination which could explain the 200 km deep high-velocity body existing under the southern Dinarides

Crustal Thinning From Orogen to Back-Arc Basin: The Structure of the Pannonian Basin Region Revealed by P-to-S Converted Seismic Waves

We present the results of P-to-S receiver function analysis to improve the 3D image of the sedimentary layer, the upper crust, and lower crust in the Pannonian Basin area. The Pannonian Basin hosts deep sedimentary depocentres superimposed on a complex basement structure and it is surrounded by mountain belts. We processed waveforms from 221 three-component broadband seismological stations. As a result of the dense station coverage, we were able to achieve so far unprecedented spatial resolution in determining the velocity structure of the crust. We applied a three-fold quality control process; the first two being applied to the observed waveforms and the third to the calculated radial receiver functions. This work is the first comprehensive receiver function study of the entire region. To prepare the inversions, we performed station-wise H-Vp/Vs grid search, as well as Common Conversion Point migration. Our main focus was then the S-wave velocity structure of the area, which we determined by the Neighborhood Algorithm inversion method at each station, where data were sub-divided into back-azimuthal bundles based on similar Ps delay times. The 1D, nonlinear inversions provided the depth of the discontinuities, shear-wave velocities and Vp/Vs ratios of each layer per bundle, and we calculated uncertainty values for each of these parameters. We then developed a 3D interpolation method based on natural neighbor interpolation to obtain the 3D crustal structure from the local inversion results. We present the sedimentary thickness map, the first Conrad depth map and an improved, detailed Moho map, as well as the first upper and lower crustal thickness maps obtained from receiver function analysis. The velocity jump across the Conrad discontinuity is estimated at less than 0.2 km/s over most of the investigated area. We also compare the new Moho map from our approach to simple grid search results and prior knowledge from other techniques. Our Moho depth map presents local variations in the investigated area: the crust-mantle boundary is at 20–26 km beneath the sedimentary basins, while it is situated deeper below the Apuseni Mountains, Transdanubian and North Hungarian Ranges (28–33 km), and it is the deepest beneath the Eastern Alps and the Southern Carpathians (40–45 km). These values reflect well the Neogene evolution of the region, such as crustal thinning of the Pannonian Basin and orogenic thickening in the neighboring mountain belts