Federated learning: A new frontier in the exploration of multi-institutional medical imaging data [0.03%]
federated学习：多机构医学影像数据探索的新前沿
Dominika Ciupek,Maciej Malawski,Tomasz Pieciak
Dominika Ciupek
Artificial intelligence has transformed the perspective of medical imaging, leading to a genuine technological revolution in modern computer-assisted healthcare systems. However, ubiquitously featured deep learning (DL) systems require acce...
Patient-specific continuous non-invasive blood pressure waveform in computed tomography derived fractional flow reserve calculation: Comparison with population-based pressure models [0.03%]
基于患者特定的连续无创血压波形的CT血流储备分数计算：与人群血压模型比较
Kryspin Mirota,Joanna Wicher-Żółtaniecka,Mateusz Rzycki et al.
Kryspin Mirota et al.
Background and objective: Fractional flow reserve (FFR) derived from coronary computed tomography angiography (FFR-CT) offers a non-invasive alternative to invasive FFR measurement, the clinical gold standard for assessin...
Noise-Pressure Constrained Liutex method for robust vortex identification in 4D Flow MRI of abdominal aortic aneurysms [0.03%]
用于腹部主动脉瘤4D流MRI的噪声压力约束式旋涡识别方法
Chengxin Weng,Daiyang He,Siquan Cheng et al.
Chengxin Weng et al.
Introduction: Accurate identification of vortices is critical for predicting the rupture risk of abdominal aortic aneurysms (AAA). However, existing vortex identification methods perform poorly in noisy 4D Flow MRI data. ...
Deep learning-driven automatic segmentation of uterine peristalsis in intracavitary electrohysterography signals [0.03%]
基于深度学习的宫腔电子宫图信号中子宫蠕动自动分割
Juan Miguel Mira-Tomas,Alba Diaz-Martinez,Jose Alberola-Rubio et al.
Juan Miguel Mira-Tomas et al.
Background and objective: Uterine peristalsis, the rhythmic contractions of the inner layer of the myometrium during the menstrual cycle, is more challenging to identify than potent contractions during menstruation, pregn...
Predicting intrinsic clearance using deep learning-based drug-metabolic enzyme interaction features on an IVIVE-harmonized endpoint dataset [0.03%]
基于深度学习的药物代谢酶相互作用特征预测内源清除率的方法及IVIVE标准化终点数据集上的应用研究
Hyunjung Lee,Hyeonseok Kang,Jung-Woo Chae et al.
Hyunjung Lee et al.
Background and objective: Intrinsic clearance is a key pharmacokinetic parameter in drug development because it influences systemic exposure and dose selection. Conventional in vitro-in vivo extrapolation (IVIVE) approach...
Liver point cloud registration via multi-feature fusion and hyperbolic embedding for augmented reality surgical navigation [0.03%]
基于多特征融合和双曲嵌入的肝点云配准方法用于增强现实手术导航系统中
Xiangyue Yang,Baochun He,Yue Dai et al.
Xiangyue Yang et al.
Background and objective: Augmented reality surgical navigation can help surgeons precisely locate tumors, veins, arteries and other critical structures during laparoscopic liver surgery. A key step in the navigation is r...
CardioRadNet: Cardiac mass diagnosis through integrated segmentation and radiomic analysis [0.03%]
基于集成分割和影像组学的心脏肿物诊断 CardioRadNet
Meri Ferretti,Michele Pagliaccia,Andrea Baggiano et al.
Meri Ferretti et al.
Background and objective: Cardiac masses (CMs), though rare, include a wide spectrum of benign and malignant lesions that require distinct therapeutic strategies. Prior studies typically address narrow classification task...
Murat Güzel,Ömer Kaan Baykan
Murat Güzel
Background: In neuro-oncology, detecting, segmenting, and delineating the boundaries of small-volume brain metastatic foci remains a significant challenge. The lack of explicit biological information on metastasis growth ...
Pulmonary nodule growth prediction with anisotropic reaction-diffusion [0.03%]
各向异性反应扩散模型在肺结节增长预测中的应用研究
Ruichu Cai,Haifeng Zhao,Yuguang Yan et al.
Ruichu Cai et al.
Background and objective: Accurate prediction of pulmonary nodule growth is critical for early malignancy assessment and timely lung cancer diagnosis. However, pulmonary nodule growth is a complex biological process influ...