Developing an Open-Source Framework for the Quantitative Simulation of Blood Flow and Tissue Motion for Ultrafast Doppler Ultrasound [0.03%]
开发用于超快多普勒超声血流和组织运动定量仿真的开源框架
Qiang Fu,Changhui Li
Qiang Fu
Ultrafast power Doppler imaging (uPDI) has become a powerful tool for both research and clinical applications. However, existing simulation tools are insufficient for generating quantitatively accurate 3-D flow fields with tissue motion mim...
A Validation of Spatially Compounded Volumetric Ultrasound Localization Microscopy for Glomerular Imaging With Light Sheet Microscopy [0.03%]
基于光片层显微镜的体积超声定位显微镜肾小球成像技术验证
Tyler J Gildemeister,Hatim Belgharbi,Rachel W Walmer et al.
Tyler J Gildemeister et al.
Objective: Glomerular structure and microvascular function are central to kidney health, yet current clinical assessments rely largely on indirect serum markers or invasive biopsy. Imaging approaches capable of resolving ...
A Coarse-to-Fine DoubleUNet Framework with Synergistic Loss for Accurate Fetal Head Circumference Measurement [0.03%]
一种协同损失的粗细结合双UNet框架的胎儿头围自动测量方法
Xixi Liu,Xiaoyang Hu,Hao Liu
Xixi Liu
Objective: Fetal head circumference (HC) measurement is a routine and indispensable examination during pregnancy, closely associated with fetal health and maternal delivery planning. To reduce the manual workload of sonog...
Oscar Bates,Carlos Cueto,Ciaran Coleman et al.
Oscar Bates et al.
Objective: Transcranial ultrasound faces significant challenges due to the human skull, which limits both imaging and therapeutic applications. High-fidelity numerical simulations can mitigate skull-induced distortions bu...
Deep Multi-Task Attention Network for Automated, Reproducible Quantification of Carotid Plaque Burden in Ultrasound Imaging [0.03%]
一种用于超声图像中颈动脉斑块负担的自动化和可重复量化任务的深度多任务注意网络
Dawood Khan,Kanwal Bano,Hafiz Zia Ur Rehman
Dawood Khan
Carotid atherosclerotic plaque burden is a well-established biomarker of cerebrovascular and cardiovascular risk, yet its quantitative assessment from ultrasound imaging remains highly operator-dependent and poorly standardized. This study ...
A Synthetic Data-Augmented Deep Learning Framework for Robust Segmentation and Quantification of the Carotid Artery in Ultrasound Images [0.03%]
一种合成数据增强的深度学习框架 用于超声图像中颈动脉的稳健分割和量化
Pei Du,Fengqin Shen,Zeyu Lai et al.
Pei Du et al.
Objective: To address the severe limitation imposed by the scarcity of annotated data on deep learning-based automated segmentation of the carotid artery in ultrasound images, this study aimed to develop and evaluate a sy...
Deep Learning Analysis of Prenatal Ultrasound for Identification of Ventriculomegaly [0.03%]
基于深度学习的产前超声脑室增宽筛查分析研究
Youssef Megahed,Inok Lee,Robin Ducharme et al.
Youssef Megahed et al.
Objective: To develop and evaluate a deep learning model capable of detecting ventriculomegaly on prenatal ultrasound images using a foundation model pre-trained specifically on ultrasound data. ...
Phase-Dependent Passive Muscle Stretching Modulates B-Mode Ultrasound Classification of Parkinson's Disease [0.03%]
相位依赖性被动肌肉拉伸调节B超分类帕金森病
Zhuohua Qiu,Bin Zha,Yongsheng Lin et al.
Zhuohua Qiu et al.
Objective: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by tremor, rigidity and bradykinesia. Although central nervous system pathology has been extensively studied, peripheral muscul...
Toward Autonomous Histotripsy: Integrating Deep Learning Segmentation With Robotic Control for Glioblastoma [0.03%]
基于深度学习分割与机器人控制集成的脑胶质瘤自主组织焦毁损技术
Shadi Dorosti,Thomas Landry,Sidney Croul et al.
Shadi Dorosti et al.
Objective: Glioblastoma multiforme (GBM) is an aggressive brain tumor in which incomplete margin delineation during surgery can contribute to residual disease or unintended damage to healthy tissue. This study proposes an...
Differentiating Mummified Thyroid Nodules From Papillary Thyroid Carcinoma: A Machine Learning Approach Using Multi-Modal Ultrasound Radiomics [0.03%]
基于多模态超声影像组学的甲状腺囊性结节与乳头状癌鉴别诊断的机器学习方法
Yang Li,Xing Yan,Jiao Li et al.
Yang Li et al.
Objectives: This study aimed to establish a machine-learning model that integrates contrast-enhanced ultrasound (CEUS) radiomics, conventional ultrasound (US) radiomics and clinical features for distinguishing mummified t...