Radiology

[Review on ultrasonographic diagnosis of thyroid diseases based on deep learning].

In recent years, the incidence of thyroid diseases has increased significantly and ultrasound examin...

Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

Artificial intelligence, computational simulations, and extended reality, among other 21st century c...

Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study.

Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasing...

Age-Specific Diagnostic Classification of ASD Using Deep Learning Approaches.

Autism Spectrum Disorder (ASD) is a highly heterogeneous condition, due to high variance in its etio...

Deep learning for precision medicine: Guiding laser therapy in ischemic retinal diseases.

In this issue of Cell Reports Medicine, Zhao and colleagues report a multi-tasking artificial intell...

[Research Progress in the Application of Ultrasound-Guided Robot in Minimally Invasive Surgery].

With the continuous advances in modern medical technology and equipment,minimally invasive surgery (...

Prospective Evaluation of AI Triage of Pulmonary Emboli on CT Pulmonary Angiograms.

Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of pulmona...

Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis.

Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjectiv...

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disea...

[To promote the clinical application of PET/MRI in oncology].

PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the...

Impact of a reduced iodine load with deep learning reconstruction on abdominal MDCT.

To evaluate the impact of a reduced iodine load using deep learning reconstruction (DLR) on the hepa...

Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination.

OBJECTIVE: Prenatal diagnosis of a rare disease on ultrasound relies on a physician's ability to rem...

Framework Development for Patient-Specific Compliant Aortic Dissection Phantom Model Fabrication: Magnetic Resonance Imaging Validation and Deep-Learning Segmentation.

Type B aortic dissection is a life-threatening medical emergency that can result in rupture of the a...

Mammography-based Deep Learning for Breast Cancer Risk Assessment for Supplemental MRI Screening.

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Background Access to supplemental screening breast MRI is determined using traditional risk models, ...

Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI.

Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisi...

Functional MRI Assessment of Brain Activity During Hand Rehabilitation with an MR-Compatible Soft Glove in Chronic Stroke Patients: A Preliminary Study.

Brain plasticity plays a significant role in functional recovery after stroke, but the specific bene...

MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer.

Prostate cancer (PCa) is a pernicious tumor with high heterogeneity, which creates a conundrum for m...

Deep Learning for Multi-Tissue Segmentation and Fully Automatic Personalized Biomechanical Models from BACPAC Clinical Lumbar Spine MRI.

STUDY DESIGN: In vivo retrospective study of fully automatic quantitative imaging feature extraction...

Technology and Tool Development for BACPAC: Qualitative and Quantitative Analysis of Accelerated Lumbar Spine MRI with Deep-Learning Based Image Reconstruction at 3T.

OBJECTIVES: To evaluate whether combining fast acquisitions with deep-learning reconstruction can pr...

Sonographer interaction with artificial intelligence: collaboration or conflict?