AIMC Topic: Neuroimaging

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Systematic protocol to identify 'clinical controls' for paediatric neuroimaging research from clinically acquired brain MRIs.

BMJ open
INTRODUCTION: Progress at the intersection of artificial intelligence and paediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and generalisable models. Retrospective analysis of clinical brain MRI scans offers a prom...

Towards Robust Brain Midline Shift Detection: A YOLO-Based 3D Slicer Extension with a Novel Dataset.

Neuroinformatics
Accurate detection of brain midline shift is critical for the diagnosis and monitoring of neurological conditions such as traumatic brain injuries, strokes, and tumors. This study aims to address the lack of dedicated datasets and tools for this task...

A radiomics model predicts progression from mild cognitive impairment to alzheimer's disease using structural MRI.

Scientific reports
The aim of this study is to build and validate a model based on structural magnetic resonance imaging (sMRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD). A total of 343 patients with MCI were selected fro...

IoMT driven Alzheimer's prediction model empowered with transfer learning and explainable AI approach in healthcare 5.0.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the primary cause of dementia, responsible for 60-70% of global cases. It severely affects memory, cognitive function, and daily independence, placing a substantial emotional an...

Multi-modal deep learning framework for early detection of Parkinson's disease using neurological and physiological data for high-fidelity diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder that remained challenging for proper diagnosis in its early stages due to its heterogeneous symptom presentation and overlapping clinical features. Consequently, there is no consens...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...

Cognitive prediction using regional connectivities and network biomarkers in Alzheimer's disease.

Neuroscience
Achieving a deep understanding of brain mechanisms requires multi-scale perspectives to capture the architecture of complex networks. In this study, we focused on patients with cognitive impairment and constructed individual brain networks from neuro...

Identifying key brain pathology in bipolar and unipolar depression using a region-specific brain aging trajectories approach: Insights from the Taiwan Aging and Mental Illness Cohort.

Psychological medicine
BACKGROUND: Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic reso...

Current imaging applications, radiomics, and machine learning modalities of CNS demyelinating disorders and its mimickers.

Journal of neurology
Distinguishing among neuroinflammatory demyelinating diseases of the central nervous system can present a significant diagnostic challenge due to substantial overlap in clinical presentations and imaging features. Collaboration between specialists, n...