Radiology

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

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Prostate Cancer Nodal Staging: Using Deep Learning to Predict Ga-PSMA-Positivity from CT Imaging Alone.

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT ...

Feb 2020 32099001
Automatic Lung Nodule Detection Combined With Gaze Information Improves Radiologists' Screening Performance.

Early diagnosis of lung cancer via computed tomography can significantly reduce the morbidity and mo...

Feb 2020 32092022
Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events...

Feb 2020 32089046
External Validation of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

RATIONALE AND OBJECTIVES: Federal legislation requires patient notification of dense mammographic br...

Feb 2020 32089465
Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine.

PURPOSE: To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitati...

Feb 2020 32070116
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains.

Ultra-high field 7T MRI scanners, while producing images with exceptional anatomical details, are co...

Feb 2020 32120269
Detecting vulnerable plaque with vulnerability index based on convolutional neural networks.

Plaque rupture and subsequent thrombosis are major processes of acute cardiovascular events. The Vul...

Feb 2020 32155412
Multi-Contrast Super-Resolution MRI Through a Progressive Network.

Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and ...

Feb 2020 32086201
Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures deri...

Feb 2020 32063026
An Integrated Robotic System for MRI-Guided Neuroablation: Preclinical Evaluation.

OBJECTIVE: Treatment of brain tumors requires high precision in order to ensure sufficient treatment...

Feb 2020 32078530
MS-Net: Multi-Site Network for Improving Prostate Segmentation With Heterogeneous MRI Data.

Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently,...

Feb 2020 32078543
Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations.

Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be pr...

Feb 2020 32064565
Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning.

OBJECTIVES: To take advantage of the deep learning algorithms to detect and calculate clot burden of...

Feb 2020 32064559
Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.

PURPOSE: Volumetric assessment of meningiomas represents a valuable tool for treatment planning and ...

Feb 2020 32060575
Inconsistent Performance of Deep Learning Models on Mammogram Classification.

OBJECTIVES: Performance of recently developed deep learning models for image classification surpasse...

Feb 2020 32068005
Assessment of knee pain from MR imaging using a convolutional Siamese network.

OBJECTIVES: It remains difficult to characterize the source of pain in knee joints either using radi...

Feb 2020 32055951
Deep learning for automated cerebral aneurysm detection on computed tomography images.

PURPOSE: Cerebrovascular aneurysms are being observed with rapidly increasing incidence. Therefore, ...

Feb 2020 32056126
Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation.

Recent advances in deep learning for medical image segmentation demonstrate expert-level accuracy. H...

Feb 2020 32070947
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