174 research outputs found
Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions
X-ray dose constantly gains interest in the interventional suite. With dose
being generally difficult to monitor reliably, fast computational methods are
desirable. A major drawback of the gold standard based on Monte Carlo (MC)
methods is its computational complexity. Besides common variance reduction
techniques, filter approaches are often applied to achieve conclusive results
within a fraction of time. Inspired by these methods, we propose a novel
approach. We down-sample the target volume based on the fraction of mass,
simulate the imaging situation, and then revert the down-sampling. To this end,
the dose is weighted by the mass energy absorption, up-sampled, and distributed
using a guided filter. Eventually, the weighting is inverted resulting in
accurate high resolution dose distributions. The approach has the potential to
considerably speed-up MC simulations since less photons and boundary checks are
necessary. First experiments substantiate these assumptions. We achieve a
median accuracy of 96.7 % to 97.4 % of the dose estimation with the proposed
method and a down-sampling factor of 8 and 4, respectively. While maintaining a
high accuracy, the proposed method provides for a tenfold speed-up. The overall
findings suggest the conclusion that the proposed method has the potential to
allow for further efficiency.Comment: 6 pages, 3 figures, Bildverarbeitung f\"ur die Medizin 202
Effective Altruism and Religion: Synergies, Tensions, Dialogue
Effective altruism has become a worldwide phenomenon. The movement combines empathy and reason in the attempt to improve the world. Adherents don’t let moral gut instincts dictate their altruistic efforts, but use evidence and reflection to do the most good they can. Effective altruism originated, and primarily grew, in strongly secular environments—such as philosophy departments or Silicon Valley. So far, a religious perspective on this movement has been lacking. What can people of faith learn from effective altruism? What may they criticise? What can effective altruism in turn take from religion? This volume offers a first examination of these questions, covering various Christian as well as Jewish and Buddhist perspectives
Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose Determined using Monte Carlo Simulations
With increasing patient and staff X-ray radiation awareness, many efforts
have been made to develop accurate patient dose estimation methods. To date,
Monte Carlo (MC) simulations are considered golden standard to simulate the
interaction of X-ray radiation with matter. However, sensitivity of MC
simulation results to variations in the experimental or clinical setup of image
guided interventional procedures are only limited studied. In particular, the
impact of patient material compositions is poorly investigated. This is mainly
due to the fact, that these methods are commonly validated in phantom studies
utilizing a single anthropomorphic phantom. In this study, we therefore
investigate the impact of patient material parameters mapping on the outcome of
MC X-ray dose simulations. A computation phantom geometry is constructed and
three different commonly used material composition mappings are applied. We
used the MC toolkit Geant4 to simulate X-ray radiation in an interventional
setup and compared the differences in dose deposition, scatter distributions
and resulting X-ray images. The evaluation shows a discrepancy between
different material composition mapping up to 20 % concerning directly
irradiated organs. These results highlight the need for standardization of
material composition mapping for MC simulations in a clinical setup.Comment: 6 pages, 4 figures, Bildverarbeitung f\"ur die Medizin 201
Dynamical cluster approximation within an augmented plane-wave framework: Spectral properties of SrVO
We present a combination of local density approximation (LDA) with the
dynamical cluster approximation (LDA+DCA) in the framework of the
full-potential linear augmented plane-wave method, and compare our LDA+DCA
results for SrVO to LDA with the dynamical mean field theory (LDA+DMFT)
calculations as well as experimental observations on SrVO. We find a
qualitative agreement of the momentum resolved spectral function with
angle-resolved photoemission spectra (ARPES) and former LDA+DMFT results. As a
correction to LDA+DMFT, we observe more pronounced coherent peaks below the
Fermi level, as indicated by ARPES experiments. In addition, we resolve the
spectral functions in the and
sectors of DCA, where band insulating and metallic phases coexist. Our approach
can be applied to correlated compounds where not only local quantum
fluctuations but also spatial fluctuations are important.Comment: 6 pages, 3 figures, accepted in Phys. Rev.
Fully-automatic CT data preparation for interventional X-ray skin dose simulation
Recently, deep learning (DL) found its way to interventional X-ray skin dose
estimation. While its performance was found to be acceptable, even more
accurate results could be achieved if more data sets were available for
training. One possibility is to turn to computed tomography (CT) data sets.
Typically, computed tomography (CT) scans can be mapped to tissue labels and
mass densities to obtain training data. However, care has to be taken to make
sure that the different clinical settings are properly accounted for. First,
the interventional environment is characterized by wide variety of table setups
that are significantly different from the typical patient tables used in
conventional CT. This cannot be ignored, since tables play a crucial role in
sound skin dose estimation in an interventional setup, e. g., when the X-ray
source is directly underneath a patient (posterior-anterior view). Second, due
to interpolation errors, most CT scans do not facilitate a clean segmentation
of the skin border. As a solution to these problems, we applied connected
component labeling (CCL) and Canny edge detection to (a) robustly separate the
patient from the table and (b) to identify the outermost skin layer. Our
results show that these extensions enable fully-automatic, generalized
pre-processing of CT scans for further simulation of both skin dose and
corresponding X-ray projections.Comment: 6 pages, 4 figures, Bildverarbeitung f\"ur die Medizin 2020, code
will be accessible soon (url
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