Related papers: A morphological segmentation approach to determini…
I review both well established and more recent findings on the properties of bars, and their host galaxies, stemming from photometric and spectroscopic observations, and discuss how these findings can be understood in terms of a global…
In this study, the main objective is to develop an algorithm capable of identifying and delineating tumor regions in breast ultrasound (BUS) and mammographic images. The technique employs two advanced deep learning architectures, namely…
Classifying the morphologies of galaxies is an important step in understanding their physical properties and evolutionary histories. The advent of large-scale surveys has hastened the need to develop techniques for automated morphological…
We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…
Morphology is the starting point for understanding galaxies. Elmegreen et al. classified spiral galaxies into flocculent, multiple-arm, and grand-design galaxies based on the regularity of their spiral arm structure. With the release of a…
We have measured the radial light profiles and global shapes of bars using two-dimensional 3.6 $\mu m $ image decompositions for 144 face-on barred galaxies from the Spitzer Survey of Stellar Structure in Galaxies (S4G). The bar surface…
In dense clusters, higher densities at early epochs as well as physical processes, such as ram pressure stripping and tidal interactions become important, and can have direct consequences for the evolution of bars and their host disks. To…
In order to establish an objective framework for studying galaxy morphology, we have developed a quantitative two-parameter description of galactic structure that maps closely on to Hubble's original tuning fork. Any galaxy can be placed in…
We propose a novel method for discovering shape regions that strongly correlate with user-prescribed tags. For example, given a collection of chairs tagged as either "has armrest" or "lacks armrest", our system correctly highlights the…
The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in…
Mammography stands as the main screening method for detecting breast cancer early, enhancing treatment success rates. The segmentation of landmark structures in mammography images can aid the medical assessment in the evaluation of cancer…
Medical images used in clinical practice are heterogeneous and not the same quality as scans studied in academic research. Preprocessing breaks down in extreme cases when anatomy, artifacts, or imaging parameters are unusual or protocols…
An analysis of the NICMOS Deep Field shows that there is no evidence of a decline in the bar fraction beyond z~0.7, as previously claimed; both bandshifting and spatial resolution must be taken into account when evaluating the evolution of…
Morphological methods play a crucial role in remote sensing image processing, due to their ability to capture and preserve small structural details. However, most of the existing deep learning models for semantic segmentation are based on…
We study the morphologies of 3,964 galaxies and their progenitors with $M_\star > 10^{10} M_\odot$ in the reference EAGLE hydrodynamical simulation from redshifts $z=1$ to $z=0$, concentrating on the redshift evolution of the bar fraction.…
The intrinsic photometric properties of inner and outer stellar bars within 17 double-barred galaxies are thoroughly studied through a photometric analysis consisting of: i) two-dimensional multi-component photometric decompositions, and…
Recent studies used TNG50 galaxies to study bar formation, evolution, and properties like length, strength, and pattern speed. In simulations, these are typically derived from particle positions and mass distribution, neglecting stellar…
Medical imaging refers to the technologies and methods utilized to view the human body and its inside, in order to diagnose, monitor, or even treat medical disorders. This paper aims to explore the application of deep learning techniques in…
Medical image segmentation is vital to the area of medical imaging because it enables professionals to more accurately examine and understand the information offered by different imaging modalities. The technique of splitting a medical…
This work examines the evolution of bar formation in disk galaxies over the last 6 giga-years by analyzing the barred galaxy fraction as a function of key structural parameters. A representative sample of local and distant field galaxies…