Using a Conformal Water Bolus to Adjust Heating Patterns of Microwave Waveguide Applicators

Background: Hyperthermia, i.e., raising tissue temperature to 40-45°C for 60 min, has been demonstrated to increase the effectiveness of radiation and chemotherapy for cancer. Although multi-element conformal heat applicators are under development to provide more adjustable heating of contoured anatomy, to date the most often used applicator to heat superficial disease is the simple microwave waveguide. With only a single power input, the operator must be resourceful to adjust heat treatment to accommodate variable size and shape tumors spreading across contoured anatomy. Methods: We used multiphysics simulation software that couples electromagnetic, thermal and fluid dynamics physics to simulate heating patterns in superficial tumors from commercially available microwave waveguide applicators. Temperature distributions were calculated inside homogenous muscle and layered skin-fat-muscle-tumor-bone tissue loads for a typical range of applicator coupling configurations and size of waterbolus. Variable thickness waterbolus was simulated as necessary to accommodate contoured anatomy. Physical models of several treatment configurations were constructed for comparison of simulation results with experimental specific absorption rate (SAR) measurements in homogenous muscle phantom. Results: Accuracy of the simulation model was confirmed with experimental SAR measurements of three unique applicator setups. Simulations demonstrated the ability to generate a wide range of power deposition patterns with commercially available waveguide antennas by controllably varying size and thickness of the waterbolus layer. Conclusion: Heating characteristics of 915 MHz waveguide antennas can be varied over a wide range by controlled adjustment of microwave power, coupling configuration, and waterbolus lateral size and thickness. The uniformity of thermal dose delivered to superficial tumors can be improved by cyclic switching of waterbolus thickness during treatment to proactively shift heat peaks and nulls around under the aperture, thereby reducing patient pain while increasing minimum thermal dose by end of treatment. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE)

Methods of evaluating the effects of coding on SAR data

It is recognized that mean square error (MSE) is not a sufficient criterion for determining the acceptability of an image reconstructed from data that has been compressed and decompressed using an encoding algorithm. In the case of Synthetic Aperture Radar (SAR) data, it is also deemed to be insufficient to display the reconstructed image (and perhaps error image) alongside the original and make a (subjective) judgment as to the quality of the reconstructed data. In this paper we suggest a number of additional evaluation criteria which we feel should be included as evaluation metrics in SAR data encoding experiments. These criteria have been specifically chosen to provide a means of ensuring that the important information in the SAR data is preserved. The paper also presents the results of an investigation into the effects of coding on SAR data fidelity when the coding is applied in (1) the signal data domain, and (2) the image domain. An analysis of the results highlights the shortcomings of the MSE criterion, and shows which of the suggested additional criterion have been found to be most important

Visualization of Skewed Data: A Tool in R

In this work we present a visualization tool specifically tailored to deal with skewed data. The technique is based upon the use of two types of notched boxplots (the usual one, and one which is tuned for the skewness of the data), the violin plot, the histogram and a nonparametric estimate of the density. The data is assumed to lie on the same line, so the plots are compatible. We show that a good deal of information can be extracted from the inspection of this tool; in particular, we apply the technique to analyze data from synthetic aperture radar images. We provide the implementation in R.Comment: Submitted to the Revista Colombiana de Estad\'istic

3D Registration of Aerial and Ground Robots for Disaster Response: An Evaluation of Features, Descriptors, and Transformation Estimation

Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior information on the environment and cannot assume the regular order of man-made environments or meaningful semantic cues. In this work we extensively evaluate different approaches to globally register UGV generated 3D point-cloud data from LiDAR sensors with UAV generated point-cloud maps from vision sensors. The approaches are realizations of different selections for: a) local features: key-points or segments; b) descriptors: FPFH, SHOT, or ESF; and c) transformation estimations: RANSAC or FGR. Additionally, we compare the results against standard approaches like applying ICP after a good prior transformation has been given. The evaluation criteria include the distance which a UGV needs to travel to successfully localize, the registration error, and the computational cost. In this context, we report our findings on effectively performing the task on two new Search and Rescue datasets. Our results have the potential to help the community take informed decisions when registering point-cloud maps from ground robots to those from aerial robots.Comment: Awarded Best Paper at the 15th IEEE International Symposium on Safety, Security, and Rescue Robotics 2017 (SSRR 2017

High-resolution optical and SAR image fusion for building database updating

This paper addresses the issue of cartographic database (DB) creation or updating using high-resolution synthetic aperture radar and optical images. In cartographic applications, objects of interest are mainly buildings and roads. This paper proposes a processing chain to create or update building DBs. The approach is composed of two steps. First, if a DB is available, the presence of each DB object is checked in the images. Then, we verify if objects coming from an image segmentation should be included in the DB. To do those two steps, relevant features are extracted from images in the neighborhood of the considered object. The object removal/inclusion in the DB is based on a score obtained by the fusion of features in the framework of Dempster–Shafer evidence theory

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy

The Stagger-grid: A Grid of 3D Stellar Atmosphere Models - II. Horizontal and Temporal Averaging and Spectral Line Formation

We study the implications of averaging methods with different reference depth scales for 3D hydrodynamical model atmospheres computed with the Stagger-code. The temporally and spatially averaged (hereafter denoted as ) models are explored in the light of local thermodynamic equilibrium (LTE) spectral line formation by comparing spectrum calculations using full 3D atmosphere structures with those from averages. We explore methods for computing mean stratifications from the Stagger-grid time-dependent 3D radiative hydro- dynamical atmosphere models by considering four different reference depth scales (geometrical depth, column-mass density, and two optical depth scales). Furthermore, we investigate the influence of alternative averages (logarithmic or enforced hydrostatic equilibrium, flux-weighted temperatures). For the line formation we compute curves of growth for Fe i and Fe ii lines in LTE . The resulting stratifications for the four reference depth scales can be considerably different. We find typically that in the upper atmosphere and in the superadiabatic region just below the optical surface, where the temperature and density fluctuations are highest, the differences become considerable and increase for higher Teff, lower logg, and lower [Fe/H]. The differential comparison of spectral line formation shows distinctive differences depending on which model is applied. The averages over layers of constant column-mass density yield the best mean representation for LTE line formation, while the averages on layers at constant geometrical height are the least appropriate. Unexpectedly, the usually preferred averages over layers of constant optical depth are prone to the increasing interference of the reversed granulation towards higher effective temperature, in particular at low metallicity.Comment: Accepted for publication in A&A, 18 pages, 16 figure