PURPOSE: We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (...
RATIONALE AND OBJECTIVES: The purpose of this study is to investigate the variance of women authors, specifically first and senior authorship among peer-reviewed artificial intelligence-related articles with a specific focus in breast imaging.
Ovarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classification system despite extensive research efforts. This study integrated five distinct multi-omics datasets from eight multicentric cohorts, applying a comb...
OBJECTIVES: We developed the deep neural network (DNN) model to automatically measure hallux valgus angle (HVA) and intermetatarsal angle (IMA) on foot radiographs. The objective is to assess the accuracy of the model by comparing to the manual measu...
Annals of the Royal College of Surgeons of England
Mar 13, 2024
INTRODUCTION: This study aimed to assess carer attitudes towards the use of artificial intelligence (AI) in management of fractures in paediatric patients. As fracture clinic services come under increasing pressure, innovative solutions are needed to...
Journal of imaging informatics in medicine
Mar 13, 2024
Breast cancer holds the highest diagnosis rate among female tumors and is the leading cause of death among women. Quantitative analysis of radiological images shows the potential to address several medical challenges, including the early detection an...
BACKGROUND: Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, t...
BACKGROUND: To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of ...
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