AI Medical Compendium Topic:
Magnetic Resonance Imaging

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A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases.

Journal of imaging informatics in medicine
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There is increasing availability of non-enhanced CT (NE-CT) of the brain, mainly owing to a wider utilization of Positron Emission Tomography-CT (PET-CT) in...

[Applications of artificial intelligence in radiology].

Radiologie (Heidelberg, Germany)
BACKGROUND: Artificial intelligence (AI) is increasingly finding its way into routine radiological work.

An Examination of Temporomandibular Joint Disc Displacement through Magnetic Resonance Imaging by Integrating Artificial Intelligence: Preliminary Findings.

Medicina (Kaunas, Lithuania)
This research was aimed at constructing a complete automated temporomandibular joint disc position identification system that could assist with magnetic resonance imaging disc displacement diagnosis on oblique sagittal and oblique coronal images. T...

Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.

Neuroradiology
UNLABELLED: Vestibular Schwannoma (VS) is a rare tumor with varied incidence rates, predominantly affecting the 60-69 age group. In the era of artificial intelligence (AI), deep learning (DL) algorithms show promise in automating diagnosis. However, ...

Abnormal postcentral gyrus voxel-mirrored homotopic connectivity as a biomarker of mild cognitive impairment: A resting-state fMRI and support vector machine analysis.

Experimental gerontology
BACKGROUND: While patients affected by mild cognitive impairment (MCI) exhibit characteristic voxel-mirrored homotopic connectivity (VMHC) alterations, the ability of such VMHC abnormalities to predict the diagnosis of MCI in these patients remains u...

Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans.

Scientific reports
The automatic segmentation of the pharyngeal airway space has many potential medical use, one of which is to help facilitate the creation of the Tubingen Palatal Plate. Therefore, it is of great importance to understand which methods are suitable for...

Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities.

Brain pathology (Zurich, Switzerland)
The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these mi...

RobMedNAS: searching robust neural network architectures for medical image synthesis.

Biomedical physics & engineering express
Investigating U-Net model robustness in medical image synthesis against adversarial perturbations, this study introduces RobMedNAS, a neural architecture search strategy for identifying resilient U-Net configurations. Through retrospective analysis o...

Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.

Journal of computer assisted tomography
OBJECTIVE: This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (DL)-based reconstruction techniques on MRI radiomic features compared to conventional image reconstruction techniques.

Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized select...