Radiology

Editorial for "Deep Learning k-Space-to-Image Reconstruction Facilitates High Spatial Resolution and Scan Time Reduction in Diffusion-Weighted Imaging Breast MRI".

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies.

PURPOSE: To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization t...

Recent Advances and Challenges in Enzymatic Depolymerization and Recycling of PET Wastes.

Poly (ethylene terephthalate) (PET) is one of the most commonly used plastics in daily life and vari...

Real-time guidance by deep learning of experienced operators to improve the standardization of echocardiographic acquisitions.

AIMS: Impaired standardization of echocardiograms may increase inter-operator variability. This stud...

Trapdoor endarterectomy for coral reef plaque of the paravisceral aorta in the modern era.

Coral reef atherosclerosis of the paravisceral aorta is a rare disease whose description is confined...

Toward a deep learning-based magnetic resonance imaging only workflow for postimplant dosimetry in I-125 seed brachytherapy for prostate cancer.

BACKGROUND AND PURPOSE: The current standard imaging-technique for creating postplans in seed prosta...

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

OBJECTIVES: The current study developed an ultrasound-based deep learning model to make preoperative...

A Lightweight Deep Learning Framework for Automatic MRI Data Sorting and Artifacts Detection.

The purpose of this study is to develop a lightweight and easily deployable deep learning system for...

Robotic tomographic ultrasound and artificial intelligence for management of haemodialysis arteriovenous fistulae.

BACKGROUND: Arteriovenous fistulae (AVF) and Arteriovenous Grafts (AVG) may present a problematic va...

Cerebrospinal fluid flow artifact reduction with deep learning to optimize the evaluation of spinal canal stenosis on spine MRI.

PURPOSE: The aim of study was to employ the Cycle Generative Adversarial Network (CycleGAN) deep lea...

Artificial Intelligence-powered automatic volume calculation in medical images - available tools, performance and challenges for nuclear medicine.

Volumetry is crucial in oncology and endocrinology, for diagnosis, treatment planning, and evaluatin...

Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions.

Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conve...

Saliency of breast lesions in breast cancer detection using artificial intelligence.

The analysis of mammograms using artificial intelligence (AI) has shown great potential for assistin...

Use of deep learning to segment bolus during videofluoroscopic swallow studies.

Anatomical segmentations generated using artificial intelligence (AI) have the potential to signific...

Coronary CT Angiography in the Cath Lab: Leveraging Artificial Intelligence to Plan and Guide Percutaneous Coronary Intervention.

The role of coronary CT angiography for the diagnosis and risk stratification of coronary artery dis...

The Performance of Machine Learning for Prediction of H3K27 M Mutation in Midline Gliomas: A Systematic Review and Meta-Analysis.

BACKGROUND: Diffuse midline gliomas (DMGs) encompass a set of tumors, and those tumors with H3K27 M ...

Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.

BACKGROUND AND OBJECTIVE: Recently, deep learning (DL) algorithms showed to be promising in predicti...

Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005-2023).

BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with ...

Artificial intelligence in medical imaging is a tool for clinical routine and scientific discovery.

The emergence of powerful machine learning methodology together with an increasing amount of data co...

Densely connected convolutional networks for ultrasound image based lesion segmentation.

Delineating lesion boundaries play a central role in diagnosing thyroid and breast cancers, making r...

Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis.

BACKGROUND: This study aimed to comprehensively evaluate the accuracy and effect of computed tomogra...