Radiology

Automated ultrasound assessment of amniotic fluid index using deep learning.

The estimation of antenatal amniotic fluid (AF) volume (AFV) is important as it offers crucial infor...

Deep learning applied to two-dimensional color Doppler flow imaging ultrasound images significantly improves diagnostic performance in the classification of breast masses: a multicenter study.

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosi...

Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver.

OBJECTIVES: To train a deep learning model to differentiate between pathologically proven hepatocell...

Convolutional Neural Networks for Pediatric Refractory Epilepsy Classification Using Resting-State Functional Magnetic Resonance Imaging.

OBJECTIVE: This study aims to evaluate the performance of convolutional neural networks (CNNs) train...

Hardware Failure Prediction on Imbalanced Times Series Data : Generation of Artificial Data Using Gaussian Process and Applying LSTMFCN to Predict Broken Hardware.

Magnetic resonance imaging (MRI) systems and their continuous, failure-free operation is crucial for...

Deep learning trained algorithm maintains the quality of half-dose contrast-enhanced liver computed tomography images: Comparison with hybrid iterative reconstruction: Study for the application of deep learning noise reduction technology in low dose.

PURPOSE: This study compares the image and diagnostic qualities of a DEep Learning Trained Algorithm...

Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors.

Brain atrophy quantification plays a fundamental role in neuroinformatics since it permits studying ...

On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks.

Multi-contrast (MC) Magnetic Resonance Imaging (MRI) of the same patient usually requires long scann...

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HC...

Computer-Aided Diagnosis of Alzheimer's Disease through Weak Supervision Deep Learning Framework with Attention Mechanism.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses ...

ARDD 2020: from aging mechanisms to interventions.

Aging is emerging as a druggable target with growing interest from academia, industry and investors....

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropri...

Does Robot Navigation and Intraoperative Computed Tomography Guidance Help with Percutaneous Endoscopic Lumbar Discectomy? A Match-Paired Study.

OBJECTIVE: To evaluate the efficacy and safety of robot-assisted percutaneous endoscopic lumbar disc...

Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution.

Time-resolved MR angiography (tMRA) has been widely used for dynamic contrast enhanced MRI (DCE-MRI)...

Non-Rigid Respiratory Motion Estimation of Whole-Heart Coronary MR Images Using Unsupervised Deep Learning.

Non-rigid motion-corrected reconstruction has been proposed to account for the complex motion of the...

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.

BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by...

Can an Artificial Intelligence Decision Aid Decrease False-Positive Breast Biopsies?

This study aimed to evaluate the effect of an artificial intelligence (AI) support system on breast ...

Editorial for "Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries".

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries.

Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced st...

Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver.

Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease b...

Deep learning in spatiotemporal cardiac imaging: A review of methodologies and clinical usability.

The use of different cardiac imaging modalities such as MRI, CT or ultrasound enables the visualizat...