Peritumoral Cortex Low-Enhancement Sign on Corticomedullary Phase CT: A Distinctive Indicator of Small Renal Malignancies [0.03%]
肾小肿瘤的影像学特征：期CT皮质周边区低强化征的临床意义探讨
Jianyi Qu,Xinyan Li,Pingyi Zhu et al.
Jianyi Qu et al.
Objective: To retrospectively evaluate the diagnostic potential of the peritumoral cortex low-enhancement (PCLE) sign on corticomedullary phase (CMP) CT images for differentiating malignant from benign lesions and clear c...
Deep Learning-Based Breath-Hold and Free-Breathing Cine MRI for Comprehensive Cardiac Evaluation [0.03%]
基于深度学习的屏气和自由呼吸心脏电影MRI的全面心脏评估
Yali Wu,Wei Sun,Shiyu Wang et al.
Yali Wu et al.
Objective: To evaluate and compare scan times, measurement accuracy, and image quality (IQ) of free-breathing (FB) and breath-hold (BH) deep learning (DL) cine MRI sequences versus standard cine MRI, with a specific focus...
Multimodal Large Language Models in Medical Imaging: Current State and Future Directions [0.03%]
多模态大型语言模型在医学影像中的现状与未来方向
Yoojin Nam,Dong Yeong Kim,Sunggu Kyung et al.
Yoojin Nam et al.
Multimodal large language models (MLLMs) are emerging as powerful tools in medicine, particularly in radiology, with the potential to serve as trusted artificial intelligence (AI) partners for clinicians. In radiology, these models integrat...
Seong Ho Park
Seong Ho Park
Time-of-Flight MRI Transition From 2D to 3D Fused Sequences: Noninvasive Technique for Angiographically Evaluating Pelvic Arteries in Placenta Accreta Spectrum Cases [0.03%]
从二维到三维融合序列的磁共振飞行时间成像技术在胎盘植入谱系疾病的盆腔动脉无创性评价中的应用
Pedro Teixeira Castro,Ana Paula Pinho Matos,Gerson Ribeiro et al.
Pedro Teixeira Castro et al.
Shahriar Faghani,Mana Moassefi,Pouria Rouzrokh et al.
Shahriar Faghani et al.
Artificial Intelligence Analysis of Chest Radiographs for Predicting Major Adverse Events in Patients Visiting the Emergency Department With Acute Cardiopulmonary Symptoms [0.03%]
用于评估急性心肺症状急诊患者预后的胸部X射线人工智能分析
Chanyoung Rhee,Ki Jeong Hong,Ki Hong Kim et al.
Chanyoung Rhee et al.
Objective: In this study, we investigated whether artificial intelligence (AI) analysis of chest radiographs (CXRs) can predict major adverse clinical events in patients visiting the emergency department (ED) with acute c...
Development of a Deep-Learning Model for Estimating Newborn Gestational Age via Lumbar Vertebral Segmentation on Plain Radiography [0.03%]
基于腰椎 segmentation 的新生儿胎龄深度学习估算模型的建立与发展
Sungwon Ham,Gayoung Choi,Bo-Kyung Je et al.
Sungwon Ham et al.
Objective: To develop a deep learning model for estimating newborn gestational age (GA) based on the shape of the lumbar vertebral bodies on cross-table lateral radiographs obtained on the first day after birth. ...
Accuracy of Large Language Models in Detecting Cases Requiring Immediate Reporting in Pediatric Radiology: A Feasibility Study Using Publicly Available Clinical Vignettes [0.03%]
基于公开临床案例探讨大型语言模型在儿科放射学即报病例筛查中的准确性：可行性研究
Jun Sung Park,Jisun Hwang,Pyeong Hwa Kim et al.
Jun Sung Park et al.
Objective: To evaluate the accuracy of multimodal large language models (LLMs) in detecting cases requiring immediate radiology reporting in pediatric radiology. ...
Selina Chiu,Yvonne Tsitsiou,Andrea Da Silva et al.
Selina Chiu et al.
Ovarian cancer (OC) remains one of the leading causes of gynecologic cancer-related mortality, with most patients presenting with disseminated disease, particularly within the peritoneal cavity. Standard treatment includes cytoreductive sur...