Radiology

Optimizing Artificial Intelligence Thresholds for Mammographic Lesion Detection: A Retrospective Study on Diagnostic Performance and Radiologist-Artificial Intelligence Discordance.

Artificial intelligence (AI)-based systems are increasingly being used to assist radiologists in de...

Deep Learning CAIPIRINHA-VIBE Improves and Accelerates Head and Neck MRI.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate image quality for contrast-enhanced ...

Integrating multimodal data to predict the progression of hormone-sensitive prostate cancer.

Identifying the population at risk of rapid progression from hormone-sensitive prostate cancer (HSPC...

Ultrasound image-based contrastive fusion non-invasive liver fibrosis staging algorithm.

OBJECTIVE: The diagnosis of liver fibrosis is usually based on histopathological examination of live...

A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America.

This scoping review aims to identify regulator-approved ophthalmic image analysis artificial intelli...

Free-running isotropic three-dimensional cine magnetic resonance imaging with deep learning image reconstruction.

BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is the gold standard for assessing ...

Deep learning enables fast and accurate quantification of MRI-guided near-infrared spectral tomography for breast cancer diagnosis.

The utilization of magnetic resonance (MR) im-aging to guide near-infrared spectral tomography (NIRS...

Deep learning reconstruction for improved image quality of ultra-high-resolution brain CT angiography: application in moyamoya disease.

PURPOSE: To investigate vessel delineation and image quality of ultra-high-resolution (UHR) CT angio...

Manual and automated facial de-identification techniques for patient imaging with preservation of sinonasal anatomy.

PURPOSE: Facial recognition of reconstructed computed tomography (CT) scans poses patient privacy ri...

Artificial intelligence-enabled opportunistic identification of immune checkpoint inhibitor-related adverse events using [F]FDG PET/CT.

The use of imaging in the diagnosis and treatment of thromboembolic pulmonary hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a potentially life-threatening condition, c...

Myocardial Perfusion PET-CT: There's More Here Than Meets the (A)I.

Predicting abnormal fetal growth using deep learning.

Ultrasound assessment of fetal size and growth is the mainstay of monitoring fetal well-being during...

Evaluation of vascular cognitive impairment and identification of imaging markers using machine learning: a multimodal MRI study.

BACKGROUND: Vascular cognitive impairment (VCI) is prevalent but underdiagnosed due to its heterogen...

Bi-modal ultrasound radiomics and habitat analysis enhanced the pre-operative prediction of axillary lymph node burden in patients with early-stage breast cancer.

OBJECTIVE: This study aimed to evaluate the value of habitat analysis based bi-modal ultrasound radi...

TFKT V2: task-focused knowledge transfer from natural images for computed tomography perceptual image quality assessment.

PURPOSE: The accurate assessment of computed tomography (CT) image quality is crucial for ensuring d...

Computed Tomography-Based Radiomics Diagnostic Model for Fat-Poor Small Renal Tumor Subtypes.

Differentiating histologic subtypes of fat-poor small renal masses using conventional imaging remai...

Multi-Scale Vision Transformer with Optimized Feature Fusion for Mammographic Breast Cancer Classification.

: Breast cancer remains one of the leading causes of mortality among women worldwide, highlighting t...

The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer.

Differentiation of adrenal incidentalomas (AIs) remains a challenge in the oncological setting. The...

Deep learning detection of acute and sub-acute lesion activity from single-timepoint conventional brain MRI in multiple sclerosis.

Multiple sclerosis (MS) is a chronic inflammatory disease characterized by demyelinating lesions in ...

A deep learning model for accurate segmentation of the Drosophila melanogaster brain from Micro-CT imaging.

The use of microcomputed tomography (Micro-CT) for imaging biological samples has burgeoned in the p...