Results 111 to 120 of about 13,088 (235)
Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1313-1322, September 2026.ABSTRACT Purpose To propose a new method using a physics‐guided neural network for quantitative parameter mapping in balanced steady‐state free precession (bSSFP) imaging. Theory and Methods We trained physics‐guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters (T1, T2,Meffc, ∆f and φRF ...
Hye‐Ryeong Choi +2 more
wiley +1 more source
Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1323-1332, September 2026.ABSTRACT Purpose The Unadjusted Langevin Algorithm (ULA) in combination with diffusion models can generate high quality MRI reconstructions with uncertainty estimation from highly undersampled k‐space data. However, sampling methods such as diffusion posterior sampling (DPS) or likelihood annealing suffer from long reconstruction times and the need for
Moritz Blumenthal +3 more
wiley +1 more source
High PSNR based Image Steganography [PDF]
International Journal of Advanced Engineering Research and Science, 2019 openaire +1 more source
Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1219-1234, September 2026.ABSTRACT Purpose To introduce SelExNet: a self‐supervised framework for two‐dimensional spatially selective excitation that jointly optimizes radiofrequency (RF) pulses and gradient waveforms, and extends to multi‐channel transmission MRI. Methods Building on prior RF‐only and joint RF‐gradient optimization approaches, SelExNet couples neural RF and ...
Yuliang Xiao +5 more
wiley +1 more source
Digital media pattern design compression and optimization method based on K-means clustering and LLE dimensionality reduction. [PDF]
PLoS OneLiu B, Zhou S, Sun J, Liu X, Lu W.
europepmc +1 more source
Intra‐MRI Head Motion Tracking and Correction: A Quantitative In Vivo Evaluation Framework
NMR in Biomedicine, Volume 39, Issue 9, September 2026.This framework introduces, for the first time, an in vivo quantification of intra‐MRI head tracking accuracy and precision. By comparing a markerless optical system (MOS) and fat‐signal navigators (FatNav) against a rigid registration‐based reference standard, it successfully detects subtle, axis‐specific performance differences and strengths between ...
Zakaria Zariry +10 more
wiley +1 more source
EQISP: efficient quantized image signal processing with multi-scale pyramid fusion for resource constrained embodied perception. [PDF]
Front NeurorobotYang T +5 more
europepmc +1 more source
Compact Snapshot Hyperspectral Imaging With Neural Dispersion‐Engineered Metalens
Nanophotonics, Volume 15, Issue 15, 13 August 2026.A dispersion‐engineered metalens, designed via an end‐to‐end deep learning framework, encodes spectral information through wavelength‐dependent PSF shifts. Fabricated by two‐photon grayscale lithography, the ultrathin device demonstrates outstanding spatial‐spectral reconstruction in both indoor and outdoor scenes, positioning it as a promising ...
Peng Liu, Jiaru Chu, Yuhang Chen
wiley +1 more source
Hybrid deep learning framework for image restoration in Fso systems affected by log-normal fading. [PDF]
Sci RepSoliman FA +3 more
europepmc +1 more source
Scanner‐agnostic artificial intelligence approach for fast bone scintigraphy
Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.Abstract Purpose Current bone scintigraphy protocols often demand full‐count, 10–15 min scans to preserve image quality, and existing deep‐learning (DL) denoisers typically need to be retrained or retuned for each camera manufacturer. We introduce a scanner‐agnostic adaptive‐diffusion U‐Net designed to reconstruct diagnostic‐grade images from half‐time
Vinicius de Oliveira Menezes +9 more
wiley +1 more source