Radiology

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

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Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models.

PURPOSE: Osteoporosis is the systematic degeneration of the human skeleton, with consequences rangin...

Selective ensemble methods for deep learning segmentation of major vessels in invasive coronary angiography.

BACKGROUND: Invasive coronary angiography (ICA) is a primary imaging modality that visualizes the lu...

Robot-assisted spinal augmentation procedures: is it worth the increased effort?

PURPOSE: Spinal augmentation procedures (SAP) are standard procedures for vertebral compression frac...

Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing.

Artificial intelligence (AI) has been making a significant impact on cardiovascular imaging, transfo...

AI/ML in Precision Medicine: A Look Beyond the Hype.

Artificial Intelligence (AI) and Machine Learning (ML) are making headlines in medical research, esp...

Development and clinical validation of deep learning for auto-diagnosis of supraspinatus tears.

BACKGROUND: Accurately diagnosing supraspinatus tears based on magnetic resonance imaging (MRI) is c...

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery.

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying...

Deep learning for assessing image quality in bi-parametric prostate MRI: A feasibility study.

BACKGROUND: Although systems such as Prostate Imaging Quality (PI-QUAL) have been proposed for quali...

Review on deep learning fetal brain segmentation from Magnetic Resonance images.

Brain segmentation is often the first and most critical step in quantitative analysis of the brain f...

Artificial intelligence-aided optical imaging for cancer theranostics.

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accu...

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal steno...

Evaluation of automated detection of head position on lateral cephalometric radiographs based on deep learning techniques.

BACKGROUND: Lateral cephalometric radiograph (LCR) is crucial to diagnosis and treatment planning of...

How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders.

PURPOSE: In this study we investigate how patients perceive the interaction between artificial intel...

Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging.

Machine-learning models for medical tasks can match or surpass the performance of clinical experts. ...

Using deep learning-derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data.

OBJECTIVES: Siamese neural networks (SNN) were used to classify the presence of radiopaque beads as ...

Joint liver and hepatic lesion segmentation in MRI using a hybrid CNN with transformer layers.

UNLABELLED: Backgound and Objective: Deep learning-based segmentation of the liver and hepatic lesio...

A deep learning approach for radiological detection and classification of radicular cysts and periapical granulomas.

OBJECTIVES: Dentists and oral surgeons often face difficulties distinguishing between radicular cyst...

In situ sensing physiological properties of biological tissues using wireless miniature soft robots.

Implanted electronic sensors, compared with conventional medical imaging, allow monitoring of advanc...

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