Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.

Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely dia...

Ensemble fuzzy deep learning for brain tumor detection.

This research presents a novel ensemble fuzzy deep learning approach for brain Magnetic Resonance Im...

Comparison of surgical approaches to the hippocampal formation with artificial intelligence.

The relatively complex functional anatomy of the mediobasal temporal region makes surgical approache...

Artificial intelligence in the diagnosis of uveal melanoma: advances and applications.

Advancements in machine learning and deep learning have the potential to revolutionize the diagnosis...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.

OBJECTIVES: Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of ...

IRMA: Machine learning-based harmonization of F-FDG PET brain scans in multi-center studies.

PURPOSE: Center-specific effects in PET brain scans arise due to differences in technical and proced...

Deep learning-based time-of-flight (ToF) enhancement of non-ToF PET scans for different radiotracers.

AIM: To evaluate a deep learning-based time-of-flight (DLToF) model trained to enhance the image qua...

Automated quantification of brain PET in PET/CT using deep learning-based CT-to-MR translation: a feasibility study.

PURPOSE: Quantitative analysis of PET images in brain PET/CT relies on MRI-derived regions of intere...

Deep learning based coronary vessels segmentation in X-ray angiography using temporal information.

Invasive coronary angiography (ICA) is the gold standard imaging modality during cardiac interventio...

Identifying plastic materials in post-consumer food containers and packaging waste using terahertz spectroscopy and machine learning.

Accurate identification of plastic materials from post-consumer food container and packaging waste i...

Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques.

OBJECTIVE: Using deep learning-based techniques to overcome physical limitations and explore the pot...

A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenager...

Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for p...

Accelerating veterinary low field MRI acquisitions using the deep learning based denoising solution HawkAI.

Magnetic resonance imaging (MRI) has changed veterinary diagnosis but its long-sequence time can be ...

Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic...

Capsule network-based deep learning for early and accurate diabetic retinopathy detection.

Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition ...

Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.

State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammogra...

Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases.

Retinal images provide a non-invasive and accessible means to directly visualize human blood vessels...

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