AIMC Topic: Magnetic Resonance Imaging
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Characterizing Brain-Cardiovascular Aging Using Multiorgan Imaging and Machine Learning.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Feb 19, 2025
The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the ...
Comparison of surgical approaches to the hippocampal formation with artificial intelligence.
Neurosurgical review
Feb 19, 2025
The relatively complex functional anatomy of the mediobasal temporal region makes surgical approaches to this area challenging. Several studies describe various surgical approaches, along with their combinations and modifications, to reach lesions of...
Moving Beyond CT Body Composition Analysis: Using Style Transfer for Bringing CT-Based Fully-Automated Body Composition Analysis to T2-Weighted MRI Sequences.
Investigative radiology
Feb 18, 2025
OBJECTIVES: Deep learning for body composition analysis (BCA) is gaining traction in clinical research, offering rapid and automated ways to measure body features like muscle or fat volume. However, most current methods prioritize computed tomography...
Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.
Investigative radiology
Feb 18, 2025
OBJECTIVES: Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this stud...
Automated quantification of brain PET in PET/CT using deep learning-based CT-to-MR translation: a feasibility study.
European journal of nuclear medicine and molecular imaging
Feb 18, 2025
PURPOSE: Quantitative analysis of PET images in brain PET/CT relies on MRI-derived regions of interest (ROIs). However, the pairs of PET/CT and MR images are not always available, and their alignment is challenging if their acquisition times differ c...
A simple clustering approach to map the human brain's cortical semantic network organization during task.
NeuroImage
Feb 18, 2025
Constructing task-state large-scale brain networks can enhance our understanding of the organization of brain functions during cognitive tasks. The primary goal of brain network partitioning is to cluster functionally homogeneous brain regions. Howev...
Comparative analysis for accurate multi-classification of brain tumor based on significant deep learning models.
Computers in biology and medicine
Feb 18, 2025
Brain tumours are a significant health concern, often resulting in severe cognitive and physiological impairments. Accurate detection and classification of brain tumours, including glioma, meningioma, and pituitary tumours, are crucial for effective ...
Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques.
Magma (New York, N.Y.)
Feb 18, 2025
OBJECTIVE: Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed.
A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.
Neuroscience
Feb 18, 2025
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenagers across the globe. Neuroimaging and Machine Learning (ML) advancements have revolutionized its diagnosis and treatment approaches. Although, the rese...
Accuracy of artificial intelligence in detecting tumor bone metastases: a systematic review and meta-analysis.
BMC cancer
Feb 18, 2025
BACKGROUND: Bone metastases (BM) represent a prevalent complication of tumors. Early and accurate diagnosis, however, is a significant hurdle for radiologists. Recently, artificial intelligence (AI) has emerged as a valuable tool to assist radiologis...
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