Zobrazeno 1 - 10
of 3 172
pro vyhledávání: '"Nuernberg P"'
Autor:
Murugesan, Gowtham Krishnan, McCrumb, Diana, Soni, Rahul, Kumar, Jithendra, Nuernberg, Leonard, Pei, Linmin, Wagner, Ulrike, Granger, Sutton, Fedorov, Andrey Y., Moore, Stephen, Van Oss, Jeff
AI in Medical Imaging project aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by developing nnU-Net models and providing AI-assisted segmentations for cancer radiology images. We created high-quality, AI-annotated imagi
Externí odkaz:
http://arxiv.org/abs/2409.20342
Autor:
Bruch, Roman, Vitacolonna, Mario, Nürnberg, Elina, Sauer, Simeon, Rudolf, Rüdiger, Reischl, Markus
Biomedical research increasingly relies on 3D cell culture models and AI-based analysis can potentially facilitate a detailed and accurate feature extraction on a single-cell level. However, this requires for a precise segmentation of 3D cell dataset
Externí odkaz:
http://arxiv.org/abs/2408.16471
We present and analyze a variational front-tracking method for a sharp-interface model of multiphase flow. The fluid interfaces between different phases are represented by curve networks in two space dimensions (2d) or surface clusters in three space
Externí odkaz:
http://arxiv.org/abs/2407.18529
In this work, we present a parametric finite element approximation of two-phase Navier-Stokes flow with viscoelasticity. The free boundary problem is given by the viscoelastic Navier-Stokes equations in the two fluid phases, connected by jump conditi
Externí odkaz:
http://arxiv.org/abs/2406.13566
Publikováno v:
Math. Models Methods Appl. Sci. 34 (2024) 2055--2097
This paper investigates a Cahn-Hilliard-Swift-Hohenberg system, focusing on a three-species chemical mixture subject to physical constraints on volume fractions. The resulting system leads to complex patterns involving a separation into phases as typ
Externí odkaz:
http://arxiv.org/abs/2405.01947
Autor:
Garcke, Harald, Nürnberg, Robert
Phase transition problems on curved surfaces can lead to a panopticon of fascinating patterns. In this paper we consider finite element approximations of phase field models with a spatially inhomogeneous and anisotropic surface energy density. The pr
Externí odkaz:
http://arxiv.org/abs/2403.14206
Autor:
Deckelnick, Klaus, Nürnberg, Robert
We introduce novel finite element schemes for curve diffusion and elastic flow in arbitrary codimension. The schemes are based on a variational form of a system that includes a specifically chosen tangential motion. We derive optimal $L^2$- and $H^1$
Externí odkaz:
http://arxiv.org/abs/2402.16799
Autor:
Deckelnick, Klaus, Nürnberg, Robert
We introduce a novel formulation for the evolution of parametric curves by anisotropic curve shortening flow in ${\mathbb R}^d$, $d\geq2$. The reformulation hinges on a suitable manipulation of the parameterization's tangential velocity, leading to a
Externí odkaz:
http://arxiv.org/abs/2310.02138
Publikováno v:
Numer. Math. 156 (2024) 1479--1509
We consider a sharp interface formulation for the multi-phase Mullins-Sekerka flow. The flow is characterized by a network of curves evolving such that the total surface energy of the curves is reduced, while the areas of the enclosed phases are cons
Externí odkaz:
http://arxiv.org/abs/2309.11948
Autor:
Dennis Bontempi, Leonard Nuernberg, Suraj Pai, Deepa Krishnaswamy, Vamsi Thiriveedhi, Ahmed Hosny, Raymond H. Mak, Keyvan Farahani, Ron Kikinis, Andrey Fedorov, Hugo J. W. L. Aerts
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a significant portion of the published literature lacks transparency and reproducibility, which hampers sustained progress toward clinical transl
Externí odkaz:
https://doaj.org/article/2cae5f3512684eb6ada92f6f175be401