AIMC Topic: Magnetic Resonance Imaging
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Unsupervised single-image super-resolution for infant brain MRI.
NeuroImage
Jun 21, 2025
Acquiring high-resolution (HR) MR images of infant brains is challenging due to lengthy scan times and limited subject compliance. Image super-resolution (SR) techniques can generate HR images from low-resolution (LR) inputs, reducing the need for ex...
BioTransX: A novel bi-former based hybrid model with bi-level routing attention for brain tumor classification with explainable insights.
Computers in biology and medicine
Jun 20, 2025
Brain tumors, known for their life-threatening implications, underscore the urgency of precise and interpretable early detection. Expertise remains essential for accurate identification through MRI scans due to the intricacies involved. However, the ...
Three-dimensional U-Net with transfer learning improves automated whole brain delineation from MRI brain scans of rats, mice, and monkeys.
Computers in biology and medicine
Jun 20, 2025
BACKGROUND: Automated whole-brain delineation (WBD) techniques often struggle to generalize across pre-clinical studies due to variations in animal models, magnetic resonance imaging (MRI) scanners, and tissue contrasts. We developed a 3D U-Net neura...
Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.
European radiology experimental
Jun 19, 2025
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...
Deep learning for differential diagnosis of parotid tumors based on 2.5D magnetic resonance imaging.
Annals of medicine
Jun 18, 2025
PURPOSE: Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in ...
Image-based AI tools in peripheral nerves assessment: Current status and integration strategies - A narrative review.
European journal of radiology
Jun 18, 2025
Peripheral Nerves (PNs) are traditionally evaluated using US or MRI, allowing radiologists to identify and classify them as normal or pathological based on imaging findings, symptoms, and electrophysiological tests. However, the anatomical complexity...
Shared and distinct neural signatures of feature and spatial attention.
NeuroImage
Jun 18, 2025
The debate on whether feature attention (FA) and spatial attention (SA) share a common neural mechanism remains unresolved. Previous neuroimaging studies have identified fronto-parietal-temporal attention-related regions that exhibited consistent act...
Development and validation of a deep learning-based automatic classification algorithm for the medial temporal lobe atrophy score using a multimodality cascade transformer.
Clinical radiology
Jun 17, 2025
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.
Aphasia severity prediction using a multi-modal machine learning approach.
NeuroImage
Jun 17, 2025
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 ...
Differences in resting-state functional connectivity between depressed bipolar and major depressive disorder patients: A machine learning study.
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...
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