Radiology

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

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Fully and Weakly Supervised Deep Learning for Meniscal Injury Classification, and Location Based on MRI.

Meniscal injury is a common cause of knee joint pain and a precursor to knee osteoarthritis (KOA). T...

Jul 2024 39020156
Deep learning reconstruction for zero echo time lung magnetic resonance imaging: impact on image quality and lesion detection.

AIMS: This study aimed to examine the impact of deep-learning reconstruction (DLR) on zero echo time...

Jul 2024 39112100
Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced stea...

Jul 2024 39017676
Streak artefact removal in x-ray dark-field computed tomography using a convolutional neural network.

BACKGROUND: Computed tomography (CT) relies on the attenuation of x-rays, and is, hence, of limited ...

Jul 2024 39012833
An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis.

Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurolo...

Jul 2024 39018642
Current status and future directions in artificial intelligence for nuclear cardiology.

INTRODUCTION: Myocardial perfusion imaging (MPI) is one of the most commonly ordered cardiac imaging...

Jul 2024 39001698
[OCT biomarkers in diabetic maculopathy and artificial intelligence].

Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic ret...

Jul 2024 39012371
Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors.

Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in time...

Jul 2024 39012871
A deep learning anthropomorphic model observer for a detection task in PET.

BACKGROUND: Lesion detection is one of the most important clinical tasks in positron emission tomogr...

Jul 2024 39008812
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...

Jul 2024 39013268
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...

Jul 2024 39024665
Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

OBJECTIVES: To investigate potential of enhancing image quality, maintaining interobserver consensus...

Jul 2024 39007984
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...

Jul 2024 39004645
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...

Jul 2024 39003625
Needle tracking in low-resolution ultrasound volumes using deep learning.

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

Jul 2024 39002100
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...

Jul 2024 39002423
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...

Jul 2024 39003325
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...

Jul 2024 38989919
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...

Jul 2024 39002314
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