Radiology

Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks.

The main goal of this study is to build an artificial intelligence (AI) architecture for automated e...

MRI-compatible pneumatic stimulator for sensorimotor mapping.

BACKGROUND: Two major concerns with respect to task-based motor functional magnetic resonance imagin...

Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

Synthesized medical images have several important applications. For instance, they can be used as an...

Swall-E: A robotic in-vitro simulation of human swallowing.

Swallowing is a complex physiological function that can be studied through medical imagery technique...

Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme.

BACKGROUND: For Glioblastoma (GBM), various prognostic nomograms have been proposed. This study aims...

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's ...

Sensorimotor Robotic Measures of tDCS- and HD-tDCS-Enhanced Motor Learning in Children.

Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrat...

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagn...

Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries.

Ultrasound imaging remains out of reach for most pregnant women in developing countries because it r...

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets.

Owing to improvements in image recognition via deep learning, machine-learning algorithms could even...

On medical application of neural networks trained with various types of data.

Neural networks have garnered attention over the past few years. A neural network is a typical model...

CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm.

Liver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Du...

An overview of deep learning in medical imaging focusing on MRI.

What has happened in machine learning lately, and what does it mean for the future of medical image ...

Extending 2-D Convolutional Neural Networks to 3-D for Advancing Deep Learning Cancer Classification With Application to MRI Liver Tumor Differentiation.

Deep learning (DL) architectures have opened new horizons in medical image analysis attaining unprec...

The current role of prostate multiparametric magnetic resonance imaging.

Prostate multi-parametric magnetic resonance imaging (mpMRI) has shown excellent sensitivity for Gle...

Ultra-Low-Dose F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing diagnostic qualit...

The Role of Artificial Intelligence in Interventional Oncology: A Primer.

Correlation-Aware Sparse and Low-Rank Constrained Multi-Task Learning for Longitudinal Analysis of Alzheimer's Disease.

Alzheimer's disease (AD), as a severe neurodegenerative disease, is now attracting more and more res...

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

OBJECTIVES: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-de...

Pet robot intervention for people with dementia: A systematic review and meta-analysis of randomized controlled trials.

This study aims to systematically evaluate the efficacy of Pet robot intervention (PRI) for people w...

Insulin resistance and adrenal incidentalomas: A bidirectional relationship.

An adrenal incidentaloma (AI) is an adrenal mass incidentally found via a radiological modality, ind...