Diagnostic Radiology

Artificial intelligence in gastrointestinal and hepatic imaging: past, present and future scopes.

The use of technology in medicine has grown exponentially because of the technological advancements ...

Australian perspectives on artificial intelligence in medical imaging.

INTRODUCTION: While artificial intelligence (AI) and recent developments in deep learning (DL) have ...

Multimodal molecular imaging in drug discovery and development.

In addition to individual imaging techniques, the combination and integration of several imaging tec...

Novel computer aided diagnostic models on multimodality medical images to differentiate well differentiated liposarcomas from lipomas approached by deep learning methods.

BACKGROUND: Deep learning methods have great potential to predict tumor characterization, such as hi...

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging.

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-p...

Deep-learning two-photon fiberscopy for video-rate brain imaging in freely-behaving mice.

Scanning two-photon (2P) fiberscopes (also termed endomicroscopes) have the potential to transform o...

Diagnostic Accuracy of Artificial Intelligence in Glaucoma Screening and Clinical Practice.

PURPOSE: Artificial intelligence (AI) has been shown as a diagnostic tool for glaucoma detection thr...

A Machine-Learning-Based Medical Imaging Fast Recognition of Injury Mechanism for Athletes of Winter Sports.

The Beijing 2022 Winter Olympics will begin soon, which is mainly focused on winter sports. Athletes...

Speeding up the Topography Imaging of Atomic Force Microscopy by Convolutional Neural Network.

Atomic force microscopy (AFM) provides unprecedented insight into surface topography research with u...

Quantifying uncertainty in machine learning classifiers for medical imaging.

PURPOSE: Machine learning (ML) models in medical imaging (MI) can be of great value in computer aide...

Non-radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports.

INTRODUCTION: Incorporating artificial intelligence (AI) in diagnostic medical imaging reports has t...

Accelerating susceptibility-weighted imaging with deep learning by complex-valued convolutional neural network (ComplexNet): validation in clinical brain imaging.

OBJECTIVES: Susceptibility-weighted imaging (SWI) is crucial for the characterization of intracrania...

Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Hyperspectral fluorescence imaging is widely used when multiple fluorescent probes with close emissi...

Predictive classification of Alzheimer's disease using brain imaging and genetic data.

For now, Alzheimer's disease (AD) is incurable. But if it can be diagnosed early, the correct treatm...

Abnormal Degree Centrality as a Potential Imaging Biomarker for Right Temporal Lobe Epilepsy: A Resting-state Functional Magnetic Resonance Imaging Study and Support Vector Machine Analysis.

Previous studies have reported altered neuroimaging features in right temporal lobe epilepsy (rTLE)....

[Forecasts from the retort. A Greek gift of artificial intelligence : Interdisciplinary data analysis in preoperative imaging diagnostics].

The growing influence of artificial intelligence on radiology not only leads to a fundamental change...

Artificial Intelligence in Medical Imaging-Learning From Past Mistakes in Mammography.

Clinical language search algorithm from free-text: facilitating appropriate imaging.

BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropr...

Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference.

Although deep networks have been shown to perform very well on a variety of medical imaging tasks, i...

Systematic Review of Generative Adversarial Networks (GANs) for Medical Image Classification and Segmentation.

In recent years, generative adversarial networks (GANs) have gained tremendous popularity for variou...

Application of Artificial Intelligence in Cardiovascular Imaging.

During the last two decades, as computer technology has matured and business scenarios have diversif...