Radiology

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

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Artificial intelligence-based computer-aided diagnosis abnormality score trends in the serial mammography of patients with breast cancer.

PURPOSE: To explore the abnormality score trends of artificial intelligence-based computer-aided dia...

Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review.

In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particula...

Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study.

INTRODUCTION: Breast arterial calcifications (BAC) are common incidental findings on routine mammogr...

A systematic review on artificial intelligence evaluating PSMA PET scan for intraprostatic cancer.

OBJECTIVES: To assess artificial intelligence (AI) ability to evaluate intraprostatic prostate cance...

Needle tracking in low-resolution ultrasound volumes using deep learning.

PURPOSE: Clinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-...

The use of artificial intelligence in musculoskeletal ultrasound: a systematic review of the literature.

PURPOSE: To systematically review the use of artificial intelligence (AI) in musculoskeletal (MSK) u...

Mass detection in automated three dimensional breast ultrasound using cascaded convolutional neural networks.

PURPOSE: Early detection of breast cancer has a significant effect on reducing its mortality rate. F...

Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.

To retrospectively assess the effectiveness of deep learning (DL) model, based on breast magnetic re...

Motion Artifact Detection for T1-Weighted Brain MR Images Using Convolutional Neural Networks.

Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as nois...

deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks.

BACKGROUND: Brain extraction in magnetic resonance imaging (MRI) data is an important segmentation s...

Deep Learning Reconstruction of Accelerated MRI: False-Positive Cartilage Delamination Inserted in MRI Arthrography Under Traction.

OBJECTIVES: The radiological imaging industry is developing and starting to offer a range of novel a...

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence.

Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of ruptu...

Advancing Medical Imaging Research Through Standardization: The Path to Rapid Development, Rigorous Validation, and Robust Reproducibility.

Artificial intelligence (AI) has made significant advances in radiology. Nonetheless, challenges in ...

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound ...

Cell recognition based on features extracted by AFM and parameter optimization classifiers.

Intelligent technology can assist in the diagnosis and treatment of disease, which would pave the wa...

A spatio-temporal graph convolutional network for ultrasound echocardiographic landmark detection.

Landmark detection is a crucial task in medical image analysis, with applications across various fie...

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