Results 191 to 200 of about 48,579 (315)

Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET. [PDF]

Hum Brain Mapp
Moon J, Kim S, Chung H, Jang I, Alzheimer's Disease Neuroimaging Initiative.   +4 more
europepmc   +1 more source

SSIM metodo taikymas didelių vaizdų analizei

, 2013
Darbe nagrinėjamas vienas iš vaizdų kokybės vertinimo metodų (metrikų) – SSIM (struktūrinio panašumo) indekso metodas bei šio metodo naudojimas tiriant didelius vaizdus. Darbo eigoje: • nustatyta kai kurių įgyvendintų SSIM indekso algoritmų problematika, vertinant aukštos raiškos vaizdus; • nustatytos gaunamų skaitinių reikšmių priklausomybės nuo ...
openaire   +1 more source

A Spatio‐Temporal Diffusion Model for Cardiac Real‐Time Imaging

Magnetic Resonance in Medicine, Volume 95, Issue 6, Page 3574-3583, June 2026.
ABSTRACT Purpose Real‐time imaging of cardiac function is favorable due to shorter scan times and becomes necessary when arrhythmia or inability to hold breath leads to insufficient quality of electrocardiogram (ECG)‐gated Cartesian cine. However, comparable spatio‐temporal resolution can only be achieved in undersampled settings, which in turn demand ...
Oliver Schad, Julius Frederik Heidenreich, Nils Petri, Viktor Hartung, Alena Kollmann, Thorsten Alexander Bley, Peter Nordbeck, Bernhard Petritsch, Tobias Wech   +8 more
wiley   +1 more source

Efficient combined SSIM- and landmark-driven image registration in a variational framework

, 2019
Jorge Larrey-Ruiz, Juan Morales‐Sánchez, L. Larrey-Ruiz   +2 more
openalex   +1 more source

Physics‐informed multimodal learning for snapshot dental spectral reflectance prediction

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Accurate color matching is essential to achieving aesthetically realistic outcomes in dental crown and bridge restorations. Traditional visual methods, however, are often affected by lighting variations and observer subjectivity. These limitations can lead to metamerism and inconsistent clinical outcomes.
Yujun Feng, Yushan Guo, Qingyi Liu, Fei Liu, Jiefei Shen, Junfei Shen   +5 more
wiley   +1 more source

Reference-guided MRI super-resolution with dual attention aggregation network. [PDF]

Front Neurol
Wang L, Chang T, Tan L, Shi B, Zhu Y.
europepmc   +1 more source

Diffusion model‐regularized implicit neural representation for computed tomography metal artifact reduction

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Computed tomography (CT) images are often severely corrupted by artifacts in the presence of metals. Existing supervised metal artifact reduction (MAR) approaches suffer from performance instability on known data due to their reliance on limited paired metal‐clean data, which limits their clinical applicability. Moreover, existing unsupervised
Jie Wen, Chenhe Du, Xiao Wang, Yuyao Zhang   +3 more
wiley   +1 more source

Systemic stomatal immunity: the beacon of fire and smoke in plant disease resistance. [PDF]

Adv Biotechnol (Singap)
Liu C, Yu Q, Song S, Qi T.
europepmc   +1 more source

Dynamic video rate adaptation based on pre-congestion notification [PDF]

, 2012
De Turck, Filip, Latré, Steven
core  

Diffusional magnetic resonance imaging anonymizing with variational autoencoder

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Anonymization is a crucial de‐identification technique that protects data privacy while ensuring its utility for model building. Current generative models such as generative adversarial networks and variational auto‐encoders (VAEs) have been applied to medical image anonymization but mainly focus on general image features, lacking specificity ...
Yunheng Shen, Ling Zheng, Ruohan Liu, Haoran Feng, Hairong Lv   +4 more
wiley   +1 more source