Results 121 to 130 of about 54,446 (214)

Accelerating 2D Kidney Magnetic Resonance Fingerprinting Using Deep Learning Based Tissue Quantification

Journal of Magnetic Resonance Imaging, Volume 63, Issue 2, Page 525-535, February 2026.
ABSTRACT Background Magnetic Resonance Fingerprinting (MRF) is a technique that can provide rapid quantification of multiple tissue properties. Deep learning may potentially contribute to an accelerated acquisition of MRF. Purpose (1) To develop a deep learning method to accelerate the acquisition for kidney MRF; (2) to evaluate its performance in ...
Zhiqing Yin, Huay Din, Jessie E. P. Sun, Christina J. MacAskill, Sree Harsha Tirumani, Pew‐Thian Yap, Mark Griswold, Chris A. Flask, Yong Chen   +8 more
wiley   +1 more source

Artificial Intelligence in Multimedia Content Generation: A Review of Audio and Video Synthesis Techniques

Journal of the Society for Information Display, Volume 34, Issue 2, Page 49-67, February 2026.
Modern AI systems can now synthesize coherent multimedia experiences, generating video and audio directly from text prompts. These unified frameworks represent a rapid shift toward controllable and synchronized content creation. From early neural architectures to transformer and diffusion paradigms, this paper contextualizes the ongoing evolution of ...
Charles Ding, Rohan Bhowmik
wiley   +1 more source

Image reconstruction and elongation artifact reduction for a dual‐panel dedicated prostate PET scanner

Medical Physics, Volume 53, Issue 2, February 2026.
Abstract Background The development of PET scanners dedicated to high temporal and spatial resolution organ‐specific imaging is an active research area, motivated by the need for cost reduction, improved lesion detectability and quantification in specific clinical scenarios, as well as by ongoing hardware and software innovations.
Abdollah Saberi Manesh, Mehdi Amini, Yazdan Salimi, Katayoun Doroud, Crispin Williams, Themistoklis Williams, Hossein Arabi, Habib Zaidi   +7 more
wiley   +1 more source

Optimized reconstruction of undersampled Dixon sequences using new memory‐efficient unrolled deep neural networks: HalfVarNet and HalfDIRCN

Magnetic Resonance in Medicine, Volume 95, Issue 2, Page 1189-1204, February 2026.
Abstract Purpose Fat fraction (FF) quantification in individual muscles using quantitative MRI is of major importance for monitoring disease progression and assessing disease severity in neuromuscular diseases. Undersampling of MRI acquisitions is commonly used to reduce scanning time. The present paper introduces novel unrolled neural networks for the
Sandra Martin, Amira Trabelsi, Maxime Guye, Marc Dubois, Redha Abdeddaim, David Bendahan, Rémi André   +6 more
wiley   +1 more source

Few‐shot learning for highly accelerated 3D time‐of‐flight MRA reconstruction

Magnetic Resonance in Medicine, Volume 95, Issue 2, Page 770-786, February 2026.
Abstract Purpose To develop a deep learning‐based reconstruction method for highly accelerated 3D time‐of‐flight MRA (TOF‐MRA) that achieves high‐quality reconstruction with robust generalization using extremely limited acquired raw data, addressing the challenge of time‐consuming acquisition of high‐resolution, whole‐head angiograms.
Hao Li, Mark Chiew, Iulius Dragonu, Peter Jezzard, Thomas W. Okell   +4 more
wiley   +1 more source

An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion

Numerical Linear Algebra with Applications, Volume 33, Issue 1, February 2026.
ABSTRACT The heat equation is often used to inpaint dropped data in inpainting‐based lossy compression schemes. We propose an alternative way to numerically solve the heat equation by an extended Krylov subspace method. The method is very efficient with respect to the computation of the solution of the heat equation at large times.
Volker Grimm, Kevin Liang
wiley   +1 more source

Should all Noises Be Treated Equally: Impact of Input Noise Variability on Neural Network Robustness

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Geophysical data collected from active field sites are often contaminated by complex and heterogeneous noise, obscuring weak seismic events, and complicating automated interpretation. Although deep learning offers promising solutions for seismic processing, its performance is highly sensitive to the nature of training noise, especially under ...
S. Alsinan, M. Makarenko, S. Liu, A. Aldawood, I. Hoteit   +4 more
wiley   +1 more source

Algoritma Penyisipan Frame untuk Peningkatan Akurasi Metode Aligned Peak Signal-to-Noise Ratio dalam Pengukuran Kualitas Video

Jurnal Komputer Terapan, 2015
Pengukuran kualitas video secara objektif mampu mengatasi kekurangan penilaian kualitas secara subjektif dalam hal waktu dan tenaga yang dibutuhkan. Pengukuran secara objektif ini menggunakan sinyal video, noise, dan parameter encoder untuk memperkirakan
Yoanda Alim Syahbana, Wecka Imam Yudhystira, Syefrida Yulina   +2 more
doaj  

Adaptive fusion based deep learning framework for restoring underwater image quality using multi scale attention features. [PDF]

Sci Rep
Veeramakali T, Sayeed MS, Yogarayan S.
europepmc   +1 more source

A Comparative Evaluation of Super-Resolution Methods for Spectral Images Using Pretrained RGB Models. [PDF]

Sensors (Basel)
Shokoohi N, Fsian AN, Thomas JB, Gouton P.   +3 more
europepmc   +1 more source