Segmentation of the mandibular canal in cone-beam CT data

Accurate information about the location of the mandibular canal is essential in case of dental implant surgery. The goal of our research is to find an automatic method which can segment the mandibular canal in Cone-beam CT (CBCT). \ud Mandibular canal segmentation methods in literature using a priori shape information are, the 2D active appearance model of Rueda et al., and 3D active shape model (ASM) of Kainmueller et al. The mean distance to manual annotation of the mandibular canal of the method of Kainmueller is around 1.1mm. The best method in literature is Kim et al. with an average distance of 0.7mm.\ud We develop and evaluate five methods for mandibular canal localization. The methods, Lukas Kanade tracking (LK), B-spline registration, demon registration, 3D active shape model (ASM), and active appearance model (AAM). The ASM and AAM need corresponding points between the mandibles in the training data. We develop and evaluate two methods to find corresponding points, minimum description length (MDL) and the second shape context (SC) based registration. To improve the quality of the CBCT scans we introduce a rotational invariant edge preserving optimized anisotropic diffusion filter.\ud We evaluate the performance on 13 CBCT scans. The registration methods have an average distance to expert annotation of the canal of more than 4mm, LK tracking a distance of 3mm, AAM and ASM a distance of respectively 2.0mm and 2.3mm. The MDL method does not improve point correspondences found by the SC method, and the pre-filtering with the introduced diffusion filter does not improve the ASM result. By using location based intensity weights we improve the AAM results, to an average distance of 1.88mm. The relatively large error is due to a low number of training datasets, and low CBCT scan quality

Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT

Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data

Learning in migration management? Persistent side effects of the EUTF

acceptedVersionPeer reviewe

Planktic foraminiferal shell thinning in the Arabian Sea due to anthropogenic ocean acidification?

About one third of the anthropogenic carbon dioxide (CO<sub>2</sub>) released into the atmosphere in the past two centuries has been taken up by the ocean. As CO<sub>2</sub> invades the surface ocean, carbonate ion concentrations and pH are lowered. Laboratory studies indicate that this reduces the calcification rates of marine calcifying organisms, including planktic foraminifera. Such a reduction in calcification resulting from anthropogenic CO<sub>2</sub> emissions has not been observed, or quantified in the field yet. Here we present the findings of a study in the Western Arabian Sea that uses shells of the surface water dwelling planktic foraminifer <i>Globigerinoides ruber</i> in order to test the hypothesis that anthropogenically induced acidification has reduced shell calcification of this species. We found that light, thin-walled shells from the surface sediment are younger (based on <sup>14</sup>C and δ<sup>13</sup>C measurements) than the heavier, thicker-walled shells. Shells in the upper, bioturbated, sediment layer were significantly lighter compared to shells found below this layer. These observations are consistent with a scenario where anthropogenically induced ocean acidification reduced the rate at which foraminifera calcify, resulting in lighter shells. On the other hand, we show that seasonal upwelling in the area also influences their calcification and the stable isotope (δ<sup>13</sup>C and δ<sup>18</sup>O) signatures recorded by the foraminifera shells. Plankton tow and sediment trap data show that lighter shells were produced during upwelling and heavier ones during non-upwelling periods. Seasonality alone, however, cannot explain the <sup>14</sup>C results, or the increase in shell weight below the bioturbated sediment layer. We therefore must conclude that probably both the processes of acidification and seasonal upwelling are responsible for the presence of light shells in the top of the sediment and the age difference between thick and thin specimens

Declining Hepatitis C Virus (HCV) Incidence in Dutch Human Immunodeficiency Virus-Positive Men Who Have Sex With Men After Unrestricted Access to HCV Therapy

Background Direct-acting antivirals (DAAa) cure hepatitis C virus (HCV) infections in 95% of infected patients. Modeling studies predict that universal HCV treatment will lead to a decrease in the incidence of new infections but real-life data are lacking. The incidence of HCV among Dutch human immunodeficiency virus (HIV)–positive men who have sex with men (MSM) has been high for >10 years. In 2015 DAAs became available to all Dutch HCV patients and resulted in a rapid treatment uptake in HIV-positive MSM. We assessed whether this uptake was followed by a decrease in the incidence of HCV infections. Methods Two prospective studies of treatment for acute HCV infection enrolled patients in 17 Dutch HIV centers, having 76% of the total HIV-positive MSM population in care in the Netherlands. Patients were recru

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery