VLBA images of High Frequency Peakers

We propose a morphological classification based on the parsec scale structure of fifty-one High Frequency Peakers (HFPs) from the ``bright'' HFP sample. VLBA images at two adjacent frequencies (chosen among 8.4, 15.3, 22.2 and 43.2 GHz) have been used to investigate the morphological properties of the HFPs in the optically thin part of their spectrum. We confirm that there is quite a clear distinction between the pc-scale radio structure of galaxies and quasars: the 78% of the galaxies show a ``Double/Triple'' morphology, typical of Compact Symmetric Objects (CSOs), while the 87% of the quasars are characterised by Core-Jet or unresolved structure. This suggests that most HFP candidates identified with quasars are likely blazar objects in which a flaring self-absorbed component at the jet base was outshining the remainder of the source at the time of the selection based on the spectral shape. Among the sources classified as CSOs or candidates it is possible to find extremely young radio sources with ages of about 100 years or even less.Comment: 21 pages, 8 figures; accepted for pubblication in A&A. Paper version with full resolution images is available at http://www.ira.inaf.it/~ddallaca/orienti.p

Multipolar Planetary Nebulae: Not as Geometrically Diversified as Thought

Planetary nebulae (PNe) have diverse morphological shapes, including point-symmetric and multipolar structures. Many PNe also have complicated internal structures such as torus, lobes, knots, and ansae. A complete accounting of all the morphological structures through physical models is difficult. A first step toward such an understanding is to derive the true three-dimensional structure of the nebulae. In this paper, we show that a multipolar nebula with three pairs of lobes can explain many of such features, if orientation and sensitivity effects are taken into account. Using only six parameters - the inclination and position angles of each pair - we are able to simulate the observed images of 20 PNe with complex structures. We suggest that the multipolar structure is an intrinsic structure of PNe and the statistics of multipolar PNe has been severely underestimated in the past.Comment: 36 pages, 5 figures, 2 table

Combining Undersampled Dithered Images

Undersampled images, such as those produced by the HST WFPC-2, misrepresent fine-scale structure intrinsic to the astronomical sources being imaged. Analyzing such images is difficult on scales close to their resolution limits and may produce erroneous results. A set of ``dithered'' images of an astronomical source generally contains more information about its structure than any single undersampled image, however, and may permit reconstruction of a ``superimage'' with Nyquist sampling. I present a tutorial on a method of image reconstruction that builds a superimage from a complex linear combination of the Fourier transforms of a set of undersampled dithered images. This method works by algebraically eliminating the high order satellites in the periodic transforms of the aliased images. The reconstructed image is an exact representation of the data-set with no loss of resolution at the Nyquist scale. The algorithm is directly derived from the theoretical properties of aliased images and involves no arbitrary parameters, requiring only that the dithers are purely translational and constant in pixel-space over the domain of the object of interest. I show examples of its application to WFC and PC images. I argue for its use when the best recovery of point sources or morphological information at the HST diffraction limit is of interest.Comment: 22 pages, 9 EPS figures, submitted to PAS

PathologyGAN: Learning deep representations of cancer tissue

We apply Generative Adversarial Networks (GANs) to the domain of digital pathology. Current machine learning research for digital pathology focuses on diagnosis, but we suggest a different approach and advocate that generative models could drive forward the understanding of morphological characteristics of cancer tissue. In this paper, we develop a framework which allows GANs to capture key tissue features and uses these characteristics to give structure to its latent space. To this end, we trained our model on 249K H&E breast cancer tissue images, extracted from 576 TMA images of patients from the Netherlands Cancer Institute (NKI) and Vancouver General Hospital (VGH) cohorts. We show that our model generates high quality images, with a Frechet Inception Distance (FID) of 16.65. We further assess the quality of the images with cancer tissue characteristics (e.g. count of cancer, lymphocytes, or stromal cells), using quantitative information to calculate the FID and showing consistent performance of 9.86. Additionally, the latent space of our model shows an interpretable structure and allows semantic vector operations that translate into tissue feature transformations. Furthermore, ratings from two expert pathologists found no significant difference between our generated tissue images from real ones. The code, generated images, and pretrained model are available at https://github.com/AdalbertoCq/Pathology-GANComment: MIDL 2020 final versio

Fragmentation and Limits to Dynamical Scaling in Viscous Coarsening: An Interrupted in situ X-Ray Tomographic Study

X-Ray microtomography was used to follow the coarsening of the structure of a ternary silicate glass experiencing phase separation in the liquid state. The volumes, surfaces, mean and Gaussian curvatures of the domains of minority phase were measured after reconstruction of the 3D images and segmentation. A linear growth law of the characteristic length scale $\ell \sim t$ was observed. A detailed morphological study was performed. While dynamical scaling holds for most of the geometrical observables under study, a progressive departure from scaling invariance of the distributions of local curvatures was evidenced. The latter results from a gradual fragmentation of the structure in the less viscous phase that also leads to a power-law size distribution of isolated domains

Optical multiband surface photometry of a sample of Seyfert galaxies. I. Large-scale morphology and local environment analysis of matched Seyfert and inactive galaxy samples

Parallel analysis of the large-scale morphology and local environment of matched active and control galaxy samples plays an important role in studies of the fueling of active galactic nuclei. We carry out a detailed morphological characterization of a sample of 35 Seyfert galaxies and a matched sample of inactive galaxies in order to compare the evidence of non-axisymmetric perturbation of the potential and, in the second part of this paper, to be able to perform a multicomponent photometric decomposition of the Seyfert galaxies. We constructed contour maps, BVRcIc profiles of the surface brightness, ellipticity, and position angle, as well as colour index profiles. We further used colour index images, residual images, and structure maps, which helped clarify the morphology of the galaxies. We studied the presence of close companions using literature data. By straightening out the morphological status of some of the objects, we derived an improved morphological classification and built a solid basis for a further multicomponent decomposition of the Seyfert sample. We report hitherto undetected (to our knowledge) structural components in some Seyfert galaxies - a bar (Ark 479), an oval/lens (Mrk 595), rings (Ark 120, Mrk 376), a nuclear bar and ring (Mrk 352), and nuclear dust lanes (Mrk 590). We compared the large-scale morphology and local environment of the Seyfert sample to those of the control one and found that (1) the two samples show similar incidences of bars, rings, asymmetries, and close companions; (2) the Seyfert bars are generally weaker than the bars of the control galaxies; (3) the bulk of the two samples shows morphological evidence of non-axisymmetric perturbations of the potential or close companions; (4) the fueling of Seyfert nuclei is not directly related to the large-scale morphology and local environment of their host galaxies.Comment: Accepted for publication in A&

Design and implementation of a real-time morphological image processor prototype

Morphology, the study of form and structure, is also a method used for processing images. Morphological image processing can be used for many purposes, including edge detection, shape recognition, smoothing, and enhancement of images. A prototype for a real-time Morphological Image Processor has been developed to process 512 x 512 extended 8-bit gray scale images, using a 7 x 7 extended 8-bit gray scale mask. This prototype processor was developed jointly with another M.S. thesis candidate, Jeffrey Hanzlik. Software was also developed to allow the user to conveniently use a personal computer to transfer images to and from the Morphological Image Processor prototype and to perform a variety of image processing operations. Field programmable gate arrays have been used for the prototype, and implementing the same architecture in VLSI will allow for real-time processing of images