Related papers: A morphological segmentation approach to determini…
The tumbling pattern of a bar is the main parameter characterising its dynamics. From numerical simulations, its evolution since bar formation is tightly linked to the dark halo in which the bar is formed through dynamical friction and…
We have investigated the accuracy and reliability of six methods used to determine the length of stellar bars in galaxies or N-body simulations. All these methods use ellipse fitting and Fourier decomposition of the surface brightness. We…
We present a study of bar and host disk evolution in a dense cluster environment, based on a sample of ~800 bright (MV <= -18) galaxies in the Abell 901/2 supercluster at z~0.165. We use HST ACS F606W imaging from the STAGES survey, and…
Bars are common galactic structures in the local universe that play an important role in the secular evolution of galaxies, including the Milky Way. In particular, the velocity distribution of individual stars in our galaxy is useful to…
We investigate the dependence of occurrence of bars in galaxies on galaxy properties and environment. We use a volume-limited sample of 33,391 galaxies brighter than $M_{r}=-19.5+5$log$h$ at $0.02\le z\le0.05489$, drawn from the SDSS DR 7.…
The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means…
We study dynamics of bars in models of disk galaxies embeded in realistic dark matter halos. We find that disk thickness plays an important, if not dominant, role in the evolution and structure of the bars. We also make extensive numerical…
In this work we introduce the curvature of a galaxy brightness profile to identify its structural subcomponents in a non-parametrically fashion. Bulges, bars, disks, lens, rings and spiral arms are key to understand the formation and…
For compression fracture detection and evaluation, an automatic X-ray image segmentation technique that combines deep-learning and level-set methods is proposed. Automatic segmentation is much more difficult for X-ray images than for CT or…
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…
Given an approximately centered image of a spiral galaxy, we describe an entirely automated method that finds, centers, and sizes the galaxy and then automatically extracts structural information about the spiral arms. For each arm segment…
This paper presents the results of a high-resolution imaging survey, using both ground-based and Hubble Space Telescope images, of a complete sample of nearby barred S0--Sa galaxies in the field, with a particular emphasis on identifying…
Statistical Shape Modeling (SSM) effectively analyzes anatomical variations within populations but is limited by the need for manual localization and segmentation, which relies on scarce medical expertise. Recent advances in deep learning…
The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation. However, in large sky surveys, even the morphological classification of galaxies into two classes, like late-type (LT) and…
We present a method to simulate deep sky images, including realistic galaxy morphologies and telescope characteristics. To achieve a wide diversity of simulated galaxy morphologies, we first use the shapelets formalism to parametrize the…
We develop diagnostics to detect the presence and orientation of a bar in an edge-on disk, using its kinematical signature in the position-velocity diagram (PVD) of a spiral galaxy observed edge-on. Using a well-studied barred spiral galaxy…
Accurate segmentation of different sub-regions of gliomas including peritumoral edema, necrotic core, enhancing and non-enhancing tumor core from multimodal MRI scans has important clinical relevance in diagnosis, prognosis and treatment of…
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…
In the last few years, deep learning classifiers have shown promising results in image-based medical diagnosis. However, interpreting the outputs of these models remains a challenge. In cancer diagnosis, interpretability can be achieved by…
We present the first study of large-scale bars in clusters at intermediate redshifts (z=0.4-0.8). We compare the properties of the bars and their host galaxies in the clusters with those of a field sample in the same redshift range. We use…