Results 131 to 140 of about 20,368 (248)
ABSTRACT Purpose To develop a self‐supervised scan‐specific deep learning framework for reconstructing accelerated multiparametric quantitative MRI (qMRI). Methods We propose REFINE‐MORE (REference‐Free Implicit NEural representation with MOdel REinforcement), combining an implicit neural representation (INR) architecture with a model reinforcement ...
Ruimin Feng +3 more
wiley +1 more source
High‐Resolution Diffusion‐Weighted Imaging With Self‐Gated Self‐Supervised Unrolled Reconstruction
ABSTRACT Purpose High‐resolution diffusion‐weighted imaging (DWI) is clinically demanding. The purpose of this work is to develop an efficient self‐supervised algorithm unrolling technique for submillimeter‐resolution DWI. Methods We developed submillimeter DWI acquisition utilizing multi‐band multi‐shot EPI with diffusion shift encoding.
Zhengguo Tan +4 more
wiley +1 more source
ABSTRACT Purpose To mitigate artifacts related to motion and field changes in high‐resolution T2*$$ {T}_2^{\ast } $$‐weighted human brain imaging using servo navigation at ultra‐high fields up to 11.7 T. Methods MR‐based servo navigators were integrated into a segmented 3D‐EPI sequence to allow for prospective correction of involuntary head motion and ...
Matthias Serger +15 more
wiley +1 more source
ABSTRACT Purpose To achieve high resolution (≤ 1 mm isotropic) whole‐brain perfusion imaging at 7 T with next generation ASL pulse sequence, reconstruction algorithm, and MRI hardware. Methods We capitalized on three major innovations: (1) FLASH‐based pseudo‐Continuous ASL (pCASL) sequence with rotated golden‐angle stack‐of‐spirals (rGA‐SoS) sampling; (
Chenyang Zhao +8 more
wiley +1 more source
Abstract Background Extensive evidence has demonstrated the superior image quality achieved through deep learning‐based reconstruction algorithms. However, given their growing adoption in clinical imaging, the impact of these algorithms on radiomics model development warrants thorough investigation.
Xiaobao Hu +6 more
wiley +1 more source
A Wearable Brain–Computer Interface for Mitigating Car Sickness via Attention Shifting
Car sickness poses a major challenge in vehicular travel, yet effective nonpharmacological solutions are scarce. We developed a wearable, closed‐loop mindfulness BCI that uses real‐time EEG‐based neurofeedback to shift attention away from motion‐induced discomfort. Validated in real‐car experiments involving >100$>100$ susceptible individuals, over 83%
Jiawei Zhu +14 more
wiley +1 more source
ABSTRACT Assessing genetic structure across ocean basins is essential to understand connectivity and guide conservation in data‐deficient open‐water sharks. In this study, we examined the population genomics of Squalus cf. mitsukurii by analyzing tissue samples collected from two distant regions: California, USA (Pacific Ocean) and Pernambuco, Brazil ...
Aisni Mayumi Corrêa de Lima Adachi +11 more
wiley +1 more source
Machine Vision–Based Insect Recognition in Agriculture: A Comprehensive Review
This study explores machine vision for automated insect recognition in agriculture, leveraging deep learning and IoT integration. The review highlights real‐time pest detection methods, enhancing crop protection with minimal pesticide use. Comparative analysis of classifiers provides insights into performance and future advancements in sustainable ...
Mohammad Monirul Islam +4 more
wiley +1 more source
EQMT integrates earthquake catalog data, fault‐network geometry, engineered features, and graph embeddings in a unified framework for forecasting earthquake magnitude and occurrence time. The framework is designed to reflect inter‐fault spatial dependencies together with temporal seismic patterns, addressing limitations of approaches based only on ...
Kiymet Kaya +5 more
wiley +1 more source
Explicit Compression Degradation Estimations for Low-Sampling Single-Pixel Imaging using Hadamard Basis. [PDF]
Zhang H, Cao J, Zhou C, Yao H, Hao Q.
europepmc +1 more source

