Prognostic value of coronary CTA-based AI plaque quantification in patients undergoing transcatheter aortic valve implantation [0.03%]
冠状动脉CTA基于人工智能的斑块定量预测经导管主动脉瓣植入术患者的预后价值
Kifah Hussain,Kevin Lee,Senthil S Balasubramanian et al.
Kifah Hussain et al.
Background: Coronary artery disease can be concomitantly evaluated as part of the pre-transcatheter aortic valve implantation (TAVI) CT angiography (CTA). More recently it has been possible to perform quantitative plaque ...
Automated detection of pyogenic liver abscess and diagnosis of Klebsiella pneumoniae infection based on CECT images with deep learning: A multicenter study [0.03%]
基于CECT图像的深学习技术在肝脏脓肿自动化检测及肺炎克雷伯杆菌感染诊断中的应用：一项多中心研究
Junxi Zhou,Xiuyun Peng,Yi Yang et al.
Junxi Zhou et al.
Background: Accurate identification of bacterial pathogens in pyogenic liver abscess (PLA) remains challenging in low- and middle-income countries (LMICs). We developed and validated an artificial intelligence (AI) model ...
Gray matter microstructural abnormalities in temporal lobe epilepsy with hippocampal sclerosis and MRI negative [0.03%]
磁共振成像阴性的颞叶内侧癫痫患者灰质微结构异常研究
Wenrui Yang,Jiandong Niu,Yuhui Xiong et al.
Wenrui Yang et al.
Objective: To assess the changes of cortical microstructure in patients with temporal lobe epilepsy combined with hippocampal sclerosis (TLE-HS) and MRI-negative TLE (negative-TLE) and its correlation with clinical charac...
Deep-learning reconstructed 3D MRI for comprehensive knee assessment: Comparison with a multisequence 2D protocol at 1.5 T [0.03%]
基于深度学习的全膝关节三维MRI评估：与1.5T下多序列二维协议的比较
Elizabet Nikolova,Jonas Kroschke,Carina Obermüller et al.
Elizabet Nikolova et al.
Objective: To compare a single isotropic 3D PD-weighted fat-saturated (3D-PDFS) acquisition with a standard 2D multisequence protocol in knee MRI using deep learning reconstruction (DLR) for comprehensive assessment of kn...
Comparison of average glandular dose in mammography for patients with breast implants when using automatic or manual exposure technique [0.03%]
自动或手动曝光技术下植入假体乳腺的患者的乳房X线平片检查平均腺体剂量比较研究
Anja Šimunović Simić,Erna Alukić,Laura Jurša et al.
Anja Šimunović Simić et al.
Objective: The aim of this study was to evaluate the average glandular dose (AGD) in mammography screening of women with breast implants and to compare the AGD and image quality obtained with automatic exposure control (A...
Myocardial tissue characterization by cardiac MRI for the evaluation of heart failure with preserved ejection fraction in hypertrophic cardiomyopathy [0.03%]
心脏磁共振心肌组织表型评价肥厚型心肌病射血分数保留的心力衰竭
Xuan Ma,Tian Lan,Jiaxin Wang et al.
Xuan Ma et al.
Purpose: This study aimed to assess the utility of myocardial tissue characteristics, as identified by cardiac magnetic resonance T1 mapping, in detecting heart failure with preserved ejection fraction (HFpEF) in patients...
Corrigendum to "Keeping AI on Track: Regular monitoring of algorithmic updates in mammography" [Eur. J. Radiol. 187 (2025) 112100] [0.03%]
关于“保持AI的正确轨道：定期监测乳腺摄影算法更新”的勘误[Eur. J. Radiol. 187 (2025) 112100]
Adnan G Taib,Jonathan J James,George J W Partridge et al.
Adnan G Taib et al.
Published Erratum
European journal of radiology. 2025 Oct 1:193:112443. DOI:10.1016/j.ejrad.2025.112443 2025
Corrigendum to "Keeping AI on Track: Regular monitoring of algorithmic updates in mammography" [Eur. J. Radiol. 187 (2025) 112100] [0.03%]
关于“保持AI的正确轨道：定期监测乳腺摄影算法更新”的勘误表[Eur. J. Radiol. 187 (2025) 112100]
Adnan G Taib,Jonathan J James,George J W Partridge et al.
Adnan G Taib et al.
Published Erratum
European journal of radiology. 2025 Oct 1:193:112443. DOI:10.1016/j.ejrad.2025.112443 2025
Radiomic biomarkers for the recurrence prediction of hepatocellular carcinoma treated with postoperative TACE: A multicenter retrospective study [0.03%]
基于术后TACE的肝癌复发预测影像组学标志物的多中心回顾性研究
Lingling Zhou,Liyun Zheng,Kun Zhang et al.
Lingling Zhou et al.
Purpose: The study aims to evaluate the value of radiomics signature in predicting the recurrence risk in hepatocellular carcinoma (HCC) patients treated with postoperative adjuvant transarterial chemoembolization (PA-TAC...
Does BMI influence AI and human reader lung nodule detection in low-dose chest CT? [0.03%]
体质指数对低剂量胸部CT肺结节人工智能和阅片人检测的影响？
Nikos Sourlos,Marcel van Tuinen,Grigory Sidorenkov et al.
Nikos Sourlos et al.
Purpose: Body mass index (BMI) can influence image quality in low dose computed tomography (LDCT) through higher image noise levels. We evaluated whether BMI affects lung nodule detection by artificial intelligence (AI) s...