Results 31 to 40 of about 320 (144)

Deep Learning‐Based Dynamic Segmentation of the Left Atrium in 4D Flow MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To design a deep learning pipeline for automated, time‐resolved segmentation of the left atrium (LA) from 4D flow MRI data. Methods We studied 100 individuals including 65 patients with atrial fibrillation (AF) and 35 healthy subjects (HS) resulting in 2530 4D flow MRI time‐volumes acquired in different centers and scanners.
Jonas Leite, Tom Da‐Silva Faria, Marie Shannon Soulez, Khaoula Bouazizi, Perrine Marsac, Elie Mousseaux, Jérôme Lamy, Moussa Gueda Moussa, Olivier Piot, Jacques Feignoux, Daniel Giese, Nicolas Badenco, Estelle Gandjbakhch, Alban Redheuil, Mikaël Laredo, Emilie Bollache, Nadjia Kachenoura   +16 more
wiley   +1 more source

A Multi‐Sequence Adversarial Fusion U‐Net for Brain Tumor Image Segmentation

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
In the field of brain tumor image segmentation, in order to avoid the impact of insufficient number of training samples, the method of fusing multi‐modal MRI information before segmentation is widely used. However, when fusing different modal features, existing methods only add fixed weights to the features of each modality, resulting in insufficient ...
Jie Wang, Jinglu Hu
wiley   +1 more source

One‐Class Autoencoders for Porcelain Art Attribution: The Case of William Billingsley

Archaeometry, EarlyView.
ABSTRACT This comprehensive study explores the application of advanced machine learning techniques, specifically one‐class autoencoders, for the authentication and attribution of English porcelain artworks. Focusing primarily on the works of William Billingsley (1758–1828), one of England's most celebrated porcelain decorators, we demonstrate how ...
Hassan Ugail, Morgan Denyer, Rachel Denyer, Howell Edwards   +3 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

Basis Networks: Learning basis functions for free‐form triangulations

Computer Graphics Forum, EarlyView.
Abstract We present a framework for learning compactly supported basis functions that define tangent continuous surfaces based on coarse irregular triangle meshes. The basis functions are represented as MLPs. Smoothness of the basis functions is achieved by using the values of Loop basis functions as the parameterization of the surface.
T. Djuren, M. Alexa
wiley   +1 more source

LeafFit: Plant Assets Creation from 3D Gaussian Splatting

Computer Graphics Forum, EarlyView.
Abstract We propose LeafFit, a pipeline that converts 3D Gaussian Splatting (3DGS) of individual plants into editable, instanced mesh assets. While 3DGS faithfully captures complex foliage, its high memory footprint and lack of mesh topology make it incompatible with traditional game production workflows. We address this by leveraging the repetition of
Chang Luo, Nobuyuki Umetani
wiley   +1 more source

Survey on differential estimators for 3d point clouds

Computer Graphics Forum, EarlyView.
Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger, Thibault Lejemble, David Coeurjolly, Loïc Barthe, Nicolas Mellado   +4 more
wiley   +1 more source

Establishing Shape Correspondences: A Survey

Computer Graphics Forum, EarlyView.
Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
wiley   +1 more source

A Simple Grid‐Maps Pipeline: Restructured, Accelerated and Upgraded

Computer Graphics Forum, EarlyView.
Abstract Grid maps – spatially arranged small multiples – are a powerful tool to show complex geospatial data. Meulemans et al. (2020) introduced a pipeline for computing high‐quality grid maps that are shaped roughly according to their containing geographic outlines.
W. Meulemans
wiley   +1 more source

Advances in 4D Representation: Geometry, Motion, and Interaction

Computer Graphics Forum, EarlyView.
We survey 4D representation through three key pillars — geometry, motion, and interaction — offering a selective, representation‐centric perspective to guide researchers in choosing and customizing the right 4D representation for their tasks. Abstract We present a survey on 4D generation and reconstruction, a fast‐evolving subfield of computer graphics
M. Zhao, S. Nag, K. Wang, A. Vora, G. Ji, P. Chun, A. Mahdavi‐Amiri, H. Zhang   +7 more
wiley   +1 more source