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| http://dx.doi.org/10.1007/s10278-016-9902-0 | DOI Listing |
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Dementia Care Research and Psychosocial Factors.
Alzheimers Dement
December 2024
Infovital, Envigado, Colombia.
Background: Currently, the diagnosis of Alzheimer's disease dementia (ADD) is determined based on clinical criteria, as well as specific imaging and cerebrospinal fluid (CSF) biomarker profiles. However, healthcare professionals face a variety of challenges that hinder their application, such as the interpretation and integration or large amounts of data derived from neuropsychological assessment, the importance attributed to each source of information and the impact of unknown variables, among others. Therefore, this research focuses on the development of a computerized diagnostic tool based on Artificial Intelligence (AI), to strengthen the capacity of healthcare professionals in the identification and diagnosis of ADD.
View Article and Find Full Text PDFDementia Care Practice.
Alzheimers Dement
December 2024
Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
"Dual Perspectives" integrates multiple MRI scans, creating a nuanced synthesis of grey matter and diffusion-based regional connections. This rendering holds particular significance in the realm of Alzheimer's and dementia research by offering a comprehensive examination of data crucial for understanding these complex neurodegenerative conditions. The inclusion of grey matter provides a detailed insight into the structural composition of the brain.
View Article and Find Full Text PDFEffects and mechanisms of computerized cognitive training in Huntington's disease: protocol for a pilot study.
Neurodegener Dis Manag
January 2025
Turner Institute for Brain & Mental Health, School of Psychological Sciences, Faculty of Medicine, Nursing & Health Sciences, 18 Innovation Walk, Monash University, Clayton VIC 3800, Australia.
Huntington's disease (HD) causes progressive cognitive decline, with no available treatments. Computerized cognitive training (CCT) has shown efficacy in other populations, but its effects in HD are largely unknown. This pilot study will explore the effects and neural mechanisms of CCT in HD.
View Article and Find Full Text PDFProspective Evaluation of Accelerated Brain MRI Using Deep Learning-Based Reconstruction: Simultaneous Application to 2D Spin-Echo and 3D Gradient-Echo Sequences.
Korean J Radiol
January 2025
Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials And Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.
Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning: A Prospective Study.
Korean J Radiol
January 2025
Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T2-w FSE Dixon sequence (T2) for breast magnetic resonance imaging (MRI).
Materials And Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner. Both T2 and T2 sequences were acquired for each patient.
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