Results 151 to 160 of about 13,089 (263)

Optimal Selection of the Effective Echo Time (TEeff ) for T2‐Weighted Fast‐Spin‐Echo MRI of the Prostate at 3.0 T: Effect on Lesion Conspicuity

Journal of Magnetic Resonance Imaging, Volume 64, Issue 3, Page 616-628, September 2026.
ABSTRACT Background Clinical T 2‐weighted (T2W) MRI of prostate cancer (PCa) usually implements a 2D fast‐spin‐echo (FSE) sequence, but understanding the echo‐time‐dependent contrast behavior is not straightforward due to the complicated FSE signal evolution.
Dahan Kim, Ronard Pabi, Eric A. Borisch, Adam T. Froemming, Roger C. Grimm, Sara Hassanzadeh, Akira Kawashima, Ayumu Kido, Naoki Takahashi, John V. Thomas, Stephen J. Riederer   +10 more
wiley   +1 more source

Quantum Dot Solar Cells: Background, Progress, and Perspective. [PDF]

Micromachines (Basel)
Neupane K, Kabel J, Uddin J, Dubey R, Ojha R, Zhang D, Yap YK.   +6 more
europepmc   +1 more source

MR Imaging‐Based Biomarkers for Strength Prediction: A Statistical Shape and Architecture Modeling of Quadriceps Muscles

Journal of Magnetic Resonance Imaging, Volume 64, Issue 3, Page 685-698, September 2026.
ABSTRACT Background Muscle mass decline, associated with strength decline, is a hallmark of aging. Yet, strength decline greatly exceeds mass decline. This indicates that aspects of muscle quality and architecture—not reflected by mass—also influence force generating capacity.
Salim Bin Ghouth, Ozkan Cigdem, Valentina Mazzoli   +2 more
wiley   +1 more source

Hydrogenated Cs₂AgBiBr₆ double perovskites: a sustainable lead-free route toward high-efficiency solar cells. [PDF]

Sci Rep
Kumar A, Tannu, Bhatia H, Gupta N, Jain A, Kumar K, Goyal AK.   +6 more
europepmc   +1 more source

Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using the Preconditioned Unadjusted Langevin Algorithm

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, Tina Holliber, Jonathan I. Tamir, Martin Uecker   +3 more
wiley   +1 more source

Slowed Gompertzian ageing in long-lived C. elegans results from expansion of decrepitude, not decelerated ageing. [PDF]

Nat Commun
Zhang B, Gems D.
europepmc   +1 more source

Assessment of MR‐Induced Heating Effects in Four Common Veterinary Implants at 1.5 and 3.0 T: A Phantom Study

Veterinary Radiology &Ultrasound, Volume 67, Issue 5, September 2026.
ABSTRACT Quantitative evaluation of implant‐related heating in magnetic resonance imaging (MRI) is well standardized in human medicine, whereas evidence in veterinary medicine remains scarce. To address this gap, we measured radiofrequency (RF)‐induced heating of four used veterinary implants under controlled conditions on clinical 3.0 and 1.5 T MRI ...
Manabu Kurihara, Taichi Kimura, Kenji Yodo, Shuhei Shibukawa   +3 more
wiley   +1 more source

First-principles investigation and device simulation of TlPbI₃-based perovskite solar cells with machine learning-driven efficiency prediction. [PDF]

RSC Adv
Harun-Or-Rashid M, Etabti H, Tazwar MT, Sadik Abid MA, Shahriyar MF, Khurramov N, Nurmatovich HA, Sabirov S, Benahmedi L, Islam MM, Rahman MF.   +10 more
europepmc   +1 more source

Quantifying Perovskite Solar Cell Degradation via Machine Learning From Spatially Resolved Multimodal Luminescence Time Series

Solar RRL, Volume 10, Issue 15, 17 August 2026.
LumPerNet combines automated aging, multimodal luminescence imaging, and leakage‐aware deep learning to predict perovskite solar cell efficiency retention. By combining PLoc, PLsc, EL images, and device‐specific reference states, the framework captures degradation‐relevant optical signatures and shows that global luminescence evolution, complemented by
Giulio Barletta, Simon Ternes, Saif Ali, Zohair Abbas, Chiara Ostendi, Marialucia D’Addio, Erica Magliano, Pietro Asinari, Eliodoro Chiavazzo, Aldo Di Carlo   +9 more
wiley   +1 more source

Performance optimization and machine learning-guided parameter sensitivity analysis of lead-free KGeCl₃ perovskite solar cells. [PDF]

RSC Adv
Ahamed T, Bappy MMH, Islam MR, Uddin MS, Hossain MA, Ahammed T.   +5 more
europepmc   +1 more source