Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1148/radiol.2019194020 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Shaping the structural dynamics of motor learning through cueing during sleep.
Sleep
January 2025
UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN - Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted Memory Reactivation (TMR), involving cueing learned material during post-training sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and post-training sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during post-training sleep affects performance gains and delayed microstructural remodeling, using both standard Diffusion Tensor Imaging (DTI) and advanced Neurite Orientation Dispersion & Density Imaging (NODDI).
View Article and Find Full Text PDFIndividualized morphological covariation network aberrance associated with seizure relapse after antiseizure medication withdrawal.
Neurol Sci
January 2025
Epilepsy Center, Department of Neurology, West China Hospital of Sichuan University, Chengdu, China.
This study intents to detect graphical network features associated with seizure relapse following antiseizure medication (ASM) withdrawal. Twenty-four patients remaining seizure-free (SF-group) and 22 experiencing seizure relapse (SR-group) following ASM withdrawal as well as 46 matched healthy participants (Control) were included. Individualized morphological similarity network was constructed using T1-weighted images, and graphic metrics were compared between groups.
View Article and Find Full Text PDFImportance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.
MAGMA
January 2025
Aix Marseille Univ, CNRS, CRMBM, Marseille, France.
Objective: Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness in this field. However, the impact of reducing neural network complexity remains unexplored in the FF quantification in individual muscles.
View Article and Find Full Text PDFEffectiveness of prenatal ultrasound in fetal sex identification: a systematic review and meta-analysis.
J Ultrasound
January 2025
Department of Medical Imaging, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
This systematic review and meta-analysis aimed to assess the accuracy and success rate of ultrasound in determining fetal sex. A search was conducted on Medline, Cochrane Library, and EMBASE databases, and the reference lists of selected studies were also reviewed. Meta-analyses were performed using Revman 5.
View Article and Find Full Text PDFUpdates on Methods for Body Composition Analysis: Implications for Clinical Practice.
Curr Obes Rep
January 2025
Metabolism and Body Composition, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
Background: Recent technological advances have introduced novel methods for measuring body composition, each with unique benefits and limitations. The choice of method often depends on the trade-offs between accuracy, cost, participant burden, and the ability to measure specific body composition compartments.
Objective: To review the considerations of cost, accuracy, portability, and participant burden in reference and emerging body composition assessment methods, and to evaluate their clinical applicability.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!