AIMC Topic: Magnetic Resonance Imaging
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Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.
BMJ mental health
Jun 10, 2025
BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exhibit overlapping symptoms but require distinct treatment approaches. Advances in voxel-based morphom...
Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.
PloS one
Jun 9, 2025
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...
Contribution of Labrum and Cartilage to Joint Surface in Different Hip Deformities: An Automatic Deep Learning-Based 3-Dimensional Magnetic Resonance Imaging Analysis.
The American journal of sports medicine
Jun 7, 2025
BACKGROUND: Multiple 2-dimensional magnetic resonance imaging (MRI) studies have indicated that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for ...
Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.
Scientific reports
Jun 6, 2025
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...
Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study.
BMC medical informatics and decision making
Jun 5, 2025
BACKGROUND: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patients.
StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images.
BMC medical imaging
Jun 5, 2025
BACKGROUND AND OBJECTIVE: Stroke ranks among the leading causes of disability and death worldwide. Timely detection can reduce its impact. Machine learning delivers powerful tools for image‑based diagnosis. This study introduces StrokeNeXt, a lightwe...
A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation.
Scientific reports
Jun 5, 2025
In clinical medicine, a reliable and resource-friendly computer-aided diagnosis (CAD) method for brain tumor segmentation is essential to enhance diagnostic accuracy and therapeutic outcomes, particularly in regions with uneven healthcare resource di...
Epistasis regulates genetic control of cardiac hypertrophy.
Nature cardiovascular research
Jun 5, 2025
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...
Phenotype
Female
Aged
Male
Humans
Genetic Predisposition to Disease
Magnetic Resonance Imaging
Receptor, IGF Type 1
Heart Failure
Middle Aged
Deep Learning
Genome-Wide Association Study
Gene Regulatory Networks
Induced Pluripotent Stem Cells
Connectin
Ventricular Remodeling
Myocytes, Cardiac
Hypertrophy, Left Ventricular
Epistasis, Genetic
Recognition of flight cadets brain functional magnetic resonance imaging data based on machine learning analysis.
PloS one
Jun 5, 2025
The rapid advancement of the civil aviation industry has attracted significant attention to research on pilots. However, the brain changes experienced by flight cadets following their training remain, to some extent, an unexplored territory compared ...
Dynamically weighted graph neural network for detection of early mild cognitive impairment.
PloS one
Jun 4, 2025
Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive impairment (MCI) holds significant clinical importance for prompt intervention and treatment of AD....
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