HST and Spitzer Observations of the HD 207129 Debris Ring

A debris ring around the star HD 207129 (G0V; d = 16.0 pc) has been imaged in scattered visible light with the ACS coronagraph on the Hubble Space Telescope and in thermal emission using MIPS on the Spitzer Space Telescope at 70 microns (resolved) and 160 microns (unresolved). Spitzer IRS (7-35 microns) and MIPS (55-90 microns) spectrographs measured disk emission at >28 microns. In the HST image the disk appears as a ~30 AU wide ring with a mean radius of ~163 AU and is inclined by 60 degrees from pole-on. At 70 microns it appears partially resolved and is elongated in the same direction and with nearly the same size as seen with HST in scattered light. At 0.6 microns the ring shows no significant brightness asymmetry, implying little or no forward scattering by its constituent dust. With a mean surface brightness of V=23.7 mag per square arcsec, it is the faintest disk imaged to date in scattered light.Comment: 28 pages, 8 figure

A PCA-based automated finder for galaxy-scale strong lenses

We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to find full or partial Einstein rings. Starting from a pre-selection of potential massive galaxies, we first perform a PCA to build a set of basis vectors. The galaxy images are reconstructed using the PCA basis and subtracted from the data. We then filter the residual image with two different methods. The first uses a curvelet (curved wavelets) filter of the residual images to enhance any curved/ring feature. The resulting image is transformed in polar coordinates, centered on the lens galaxy center. In these coordinates, a ring is turned into a line, allowing us to detect very faint rings by taking advantage of the integrated signal-to-noise in the ring (a line in polar coordinates). The second way of analysing the PCA-subtracted images identifies structures in the residual images and assesses whether they are lensed images according to their orientation, multiplicity and elongation. We apply the two methods to a sample of simulated Einstein rings, as they would be observed with the ESA Euclid satellite in the VIS band. The polar coordinates transform allows us to reach a completeness of 90% and a purity of 86%, as soon as the signal-to-noise integrated in the ring is higher than 30, and almost independent of the size of the Einstein ring. Finally, we show with real data that our PCA-based galaxy subtraction scheme performs better than traditional subtraction based on model fitting to the data. Our algorithm can be developed and improved further using machine learning and dictionary learning methods, which would extend the capabilities of the method to more complex and diverse galaxy shapes

Computer-Aided Detection of Pathologically Enlarged Lymph Nodes On Non-Contrast CT In Cervical Cancer Patients For Low-Resource Settings

The mortality rate of cervical cancer is approximately 266,000 people each year, and 70% of the burden occurs in Low- and Middle- Income Countries (LMICs). Radiation therapy is the primary modality for treatment of locally advanced cervical cancer cases. In the absence of high quality diagnostic imaging needed to identify nodal metastasis, many LMIC sites treat standard pelvic fields, failing to include node metastasis outside of the field and/or to boost lymph nodes in the abdomen and pelvis. The first goal of this project was to create a program which automatically identifies positive cervical cancer lymph nodes on non-contrast daily CT images, which are widely available in LMICs(1). A region of interest which is likely to contain the nodal volumes relevant for cervical cancer was defined on a single patient CT(2). This region was deformed onto new patients using an in-house, demons-based deformation software. Edge detection and erosion filtering were used to distinguish potential positive nodes from normal structures. Regions on adjacent slices were then connected into a potential nodal 3D-structure. To differentiate these 3D structures from normal tissues, eighty-six features were generated based on the shape and mean pixel values of the structures, and four classification ensemble methods were tested to differentiate the positive nodes from normal tissues. A cohort of fifty-eight MD Anderson cervical cancer patients with pathologically enlarged lymph nodes were used as a training-test set. Similarly, twenty MD Anderson cervical cancer patients were obtained as a validation set. They contained 154 and 35 pathologically enlarged lymph nodes, respectively. Model comparison led to the selection of the Adaboost ensemble model, utilizing 17 features. In the validation set, 60% of the clinically significant positive cervical cancer nodes were identified along with a false/true positive ratio of ~4:1. The entire process takes approximately 10/number-of-cores-minutes. Our findings demonstrated that our computer-aided detection model can assist in the identification of metastatic nodal disease where high quality diagnostic imaging is not readily available. By identifying these nodes, radiation treatment fields can be modified to include pathologically enlarged lymph nodes, which is an essential element to providing potentially curative radiotherapy for cervical cancer

Using muon rings for the optical throughput calibration of the SST-1M prototype for the Cherenkov Telescope Array

Imaging Atmospheric Cherenkov Telescopes (IACTs) are ground-based instruments devoted to the study of very high energy gamma-rays coming from space. The detection technique consists of observing images created by the Cherenkov light emitted when gamma rays, or more generally cosmic rays, propagate through the atmosphere. While in the case of protons or gamma-rays the images present a filled and more or less elongated shape, energetic muons penetrating the atmosphere are visualised as characteristic circular rings or arcs. A relatively simple analysis of the ring images allows the reconstruction of all the relevant parameters of the detected muons, such as the energy, the impact parameter, and the incoming direction, with the final aim to use them to calibrate the total optical throughput of the given IACT telescope. We present the results of preliminary studies on the use of images created by muons as optical throughput calibrators of the single mirror small size telescope prototype SST-1M proposed for the Cherenkov Telescope Array.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

The CFHTLS Strong Lensing Legacy Survey: I. Survey overview and T0002 release sample

AIMS: We present data from the CFHTLS Strong Lensing Legacy Survey (SL2S). Due to the unsurpassed combined depth, area and image quality of the Canada-France-Hawaii Legacy Survey it is becoming possible to uncover a large, statistically well-defined sample of strong gravitational lenses which spans the dark halo mass spectrum predicted by the concordance model from galaxy to cluster haloes. METHODS: We describe the development of several automated procedures to find strong lenses of various mass regimes in CFHTLS images. RESULTS: The preliminary sample of about 40 strong lensing candidates discovered in the CFHTLS T0002 release, covering an effective field of view of 28 deg$^2$ is presented. These strong lensing systems were discovered using an automated search and consist mainly of gravitational arc systems with splitting angles between 2 and 15 arcsec. This sample shows for the first time that it is possible to uncover a large population of strong lenses from galaxy groups with typical halo masses of about $10^{13}h^{-1}M_\odot$. We discuss the future evolution of the SL2S project and its main scientific aims for the next 3 years, in particular our observational strategy to extract the hundreds of gravitational rings also present in these fields.Comment: 11 pages, 5 figures, A&A in pres