AIMC Topic: Neuroimaging
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Class balancing diversity multimodal ensemble for Alzheimer's disease diagnosis and early detection.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 22, 2025
Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection and diagnosis of AD are critical for delaying progression and improving patient outcomes. Traditional ...
Brain tumor segmentation with deep learning: Current approaches and future perspectives.
Journal of neuroscience methods
Mar 21, 2025
BACKGROUND: Accurate brain tumor segmentation from MRI images is critical in the medical industry, directly impacts the efficacy of diagnostic and treatment plans. Accurate segmentation of tumor region can be challenging, especially when noise and ab...
Transforming neurodegenerative disorder care with machine learning: Strategies and applications.
Neuroscience
Mar 20, 2025
Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting in diverse forms such as memory loss and movement disorders, pose significant challenges due to their complex molecular mechanisms and heterogeneous ...
Neuro_DeFused-Net: A novel multi-scale 2DCNN architecture assisted diagnostic model for Parkinson's disease diagnosis using deep feature-level fusion of multi-site multi-modality neuroimaging data.
Computers in biology and medicine
Mar 18, 2025
BACKGROUND: Neurological disorders, particularly Parkinson's Disease (PD), are serious and progressive conditions that significantly impact patients' motor functions and overall quality of life. Accurate and timely diagnosis is still crucial, but it ...
Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.
Scientific reports
Mar 18, 2025
Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving the common practice of screening for Mild Cognitive Impairment (MCI). However, the progressive nature of AD makes it challenging to identify its causa...
Masked Deformation Modeling for Volumetric Brain MRI Self-Supervised Pre-Training.
IEEE transactions on medical imaging
Mar 17, 2025
Self-supervised learning (SSL) has been proposed to alleviate neural networks' reliance on annotated data and to improve downstream tasks' performance, which has obtained substantial success in several volumetric medical image segmentation tasks. How...
Optimized attention-enhanced U-Net for autism detection and region localization in MRI.
Psychiatry research. Neuroimaging
Mar 14, 2025
Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects a child's cognitive and social skills, often diagnosed only after symptoms appear around age 2. Leveraging MRI for early ASD detection can improve intervention outcomes. Th...
A comprehensive interpretable machine learning framework for mild cognitive impairment and Alzheimer's disease diagnosis.
Scientific reports
Mar 11, 2025
An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of the ML models' interpretations. The dataset used comprises volumetric me...
Towards automatic US-MR fetal brain image registration with learning-based methods.
NeuroImage
Mar 7, 2025
Fetal brain imaging is essential for prenatal care, with ultrasound (US) and magnetic resonance imaging (MRI) providing complementary strengths. While MRI has superior soft tissue contrast, US offers portable and inexpensive screening of neurological...
Alzheimer's disease prediction using 3D-CNNs: Intelligent processing of neuroimaging data.
SLAS technology
Mar 6, 2025
Alzheimer's disease (AD) is a severe neurological illness that demolishes memory and brain functioning. This disease affects an individual's capacity to work, think, and behave. The proportion of individuals suffering from AD is rapidly increasing. I...
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