Results 101 to 110 of about 13,088 (235)

t‐Regina: Data‐driven Authoring of Free‐form Registration for Cartoon Character Sprites

Computer Graphics Forum, EarlyView.
Abstract This paper proposes t‐Regina, a novel iterative scheme that automates the manipulation of grid handles in free‐form deformation (FFD) for deformable registrations of cartoon character sprites. First, we build a data‐driven FFD (dFFD) that enables users to handle locations of FFD handles from lower‐dimensional parameters.
Tsukasa Fukusato, Akinobu Maejima
wiley   +1 more source

Tone deviation evaluation of boundary pixels static raster image using balanced extending algorithms

Системный анализ и прикладная информатика
While use algorithms of pre-processing raster image involves improving image characteristics to use qualitative transformation effect result on following processing stages.
D. V. Zaerko, N. L. Bobrova, Dm. V. Zaerko   +2 more
doaj   +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

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 more
wiley   +1 more source

Application of Noise2Inverse and adaptation (Noise2Phase) to single‐mask x‐ray phase contrast micro‐computed tomography

Journal of Microscopy, EarlyView.
Abstract X‐ray phase contrast imaging (XPCI), when implemented in micro‐computed tomography (micro‐CT) mode, offers high‐contrast 3D imaging of weakly‐attenuating material samples. In the so‐called single‐mask edge illumination approach, a mask with periodically spaced transmitting apertures is used to split the x‐ray beam into narrow beamlets; when ...
Khushal Shah, Grammatiki Lioliou, Dai Chen, Alexander Denker, Peter Munro, Marco Endrizzi, Alberto Astolfo, Alessandro Olivo, Charlotte K. Hagen   +8 more
wiley   +1 more source

3SD: Rotational symmetry single‐shot denoising in fluorescence microscopy

Journal of Microscopy, EarlyView.
Abstract Image noise is a fundamental problem in fluorescence microscopy analysis, especially in live cell imaging applications where the number of detected photons is limited due to low power of excitation lasers to prevent phototoxicity during extended imaging experiments.
Tijmen H. de Wolf, Pleun Engbers, Justine Perrin, Julie Nonnekens, Ihor Smal   +4 more
wiley   +1 more source

Zero‐Shot Self‐Supervised Learning of Single Breath‐Hold Magnetic Resonance Cholangiopancreatography (MRCP) Reconstruction

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1666-1681, October 2026.
ABSTRACT Purpose To investigate the feasibility of zero‐shot self‐supervised learning reconstruction for reducing breath‐hold times in magnetic resonance cholangiopancreatography (MRCP). Methods Breath‐hold MRCP was acquired from 11 healthy volunteers on 3T scanners using an incoherent k‐space sampling pattern, leading to a 14‐s acquisition time and an
Jinho Kim, Marcel Dominik Nickel, Florian Knoll   +2 more
wiley   +1 more source

Denoising of ASL Data Using Deep Learning Priors Generated From Distribution Remapping

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1972-1982, October 2026.
ABSTRACT Purpose To develop an effective deep learning (DL)–based method to denoise arterial spin labeling (ASL) data. Methods Conventional DL–based ASL denoising methods often suffer from overfitting and poor generalization when training data are limited.
Ziyang Xu, Rong Guo, Ziwen Ke, Yudu Li, Yibo Zhao, Wen Jin, Ruihao Liu, Ziyu Meng, Yao Li, Zhi‐Pei Liang   +9 more
wiley   +1 more source

DeepRelaxo: Fast Mono‐Exponential Magnitude Brain R2* Mapping With Reduced Echoes Using Self‐Supervised Deep Learning

Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1293-1302, September 2026.
ABSTRACT Purpose We introduce DeepRelaxo, a fast and generalizable deep learning method for estimating brain R2* maps from multi‐echo gradient echo (ME‐GRE) acquisitions with arbitrary echo configurations, including shortened echo trains for accelerated scans.
Samiha Prima, Zhuang Xiong, Alan H. Wilman, Hongfu Sun   +3 more
wiley   +1 more source

Time‐Conditioned Zero‐Shot Self‐Supervised Reconstruction for Accelerated 3D Ultra‐Low‐Field MRI

Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1303-1312, September 2026.
ABSTRACT Purpose Ultra‐low‐field (ULF) MRI provides a cost‐effective, portable imaging option but has relatively low SNR and long acquisition times compared to standard clinical scans. This study presents a time‐conditioned zero‐shot self‐supervised learning image reconstruction framework (ULF‐ZS‐SSL) to accelerate 3D‐acquired single‐coil ULF MRI ...
Mart W. J. van Straten, Beatrice Lena, Chloé Najac, Ruben van den Broek, Peter Börnert, Andrew Webb, Yiming Dong   +6 more
wiley   +1 more source