AIM: The aim of this study was to develop and validate a deep learning-based automatic classification algorithm for the medial temporal lobe atrophy (MTA) score in patients with cognitive impairment.
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI)) to predict aphasia severity using Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) in ...
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Jun 17, 2025
Nearly 60 % of individuals with bipolar disorder (BD) are initially classified as major depressive disorder (MDD) patients, resulting in inappropriate drug treatment. Identifying reliable biomarkers for the differential diagnosis between MDD and BD p...
. In radiotherapy planning, acquiring both magnetic resonance (MR) and computed tomography (CT) images is crucial for comprehensive evaluation and treatment. However, simultaneous acquisition of MR and CT images is time-consuming, economically expens...
To develop motion-resolved volumetric MRI with 1.1 mm isotropic resolution and scan times <5 min using a combination of 3D radial kooshball acquisition and spatial-temporal deep learning 4D reconstruction for free-breathing high-definition (HD) lung ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 16, 2025
This study focuses on artificial intelligence-driven classification of glioma and Ki-67 leveling using T2w-FLAIR MRI, exploring the association of Ki-67 biomarkers with deep learning (DL) features through explainable artificial intelligence (XAI) and...
Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health outcomes like cognition. However, there remains a lack of studies investigating the rate of brain aging and its relationship to cognition. Furthermore...
Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning sup...
Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types of tumors in neuro-oncology. Segmenting brain tumors is a crucial part of medical imaging. It plays a key role in diagnosing conditions, planning tre...
As deep learning continues to advance in medical analysis, the increasing complexity of models, particularly Convolutional Neural Networks (CNNs), presents significant challenges related to interpretability, computational costs, and real-world applic...
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