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Zhao, Yanzhe

0000-0001-6997-9841

Mayo Clinic

Mayo Clinic

Citations 3

Contrast-Free Ultrasound Microvascular Imaging via Radiality and Similarity Weighting
Yin, Jingyi , Zhang, Jingke , Huang, Lijie , DeRuiter, Ryan M. , Ji, Kaipeng , Zhao, Yanzhe , Knoll, Kate M , Petersen, Kendra E , Wu, Tao , Zhu, Xiang, Krier, James D., Robinson, Kathryn A. , Lerman, Lilach O. , Petersen, Kendra E. , Yin, Jingyi , Zhang, Jingke , DeRuiter, Ryan , Lok, U‐Wai , Bentall, Andrew , Chen, Shigao , Huang, Chengwu

IEEE Transactions on Ultrasonics | June 3, 2026 | Volume: 73 | Issue: 7 | Pages: 775-790

10.1109/tuson.2026.3699956 Get It

Fast 3-D Ultrasound Localization Microscopy via Projection-Based Processing Framework
Zhang, Jingke , Yin, Jingyi , Huang, Lijie , DeRuiter, Ryan M. , Ji, Kaipeng , Zhao, Yanzhe , Krier, James D., Zhu, Xiang, Lerman, Lilach O. , Yin, Jingyi , Zhang, Jingke , DeRuiter, Ryan , Lok, U‐Wai , Wu, Tao , Ji, Kaipeng, Huang, Chengwu , Chen, Shigao

IEEE Transactions on Medical Imaging | May 15, 2026 | Volume: 45 | Issue: 7 | Pages: 4105-4122

10.1109/tmi.2026.3692792 Get It

Mapping Microvascular Flow via Radon Transform Ultrasound: Technical Advances and Pilot Application
Yin, Jingyi , Huang, Lijie, Zhang, Jingke , DeRuiter, Ryan M., Zhu, Xiang-yang, Krier, James D., Kim, Y, Zhao, Y., Ji, Kaipeng , Lerman, L. O., Chen, S., Huang, Chengwu , Zhao, Yanzhe , Huang, Chengwu , Zhang, Jingke , Huang, Lijie, Lok, U‐Wai , DeRuiter, Ryan M. , Lucien, Fabrice , Lerman, Lilach O.

BME Frontiers | January 30, 2026 | Volume: 7 | Issue: No issue available | Pages: No page available

10.34133/bmef.0234 Get It

Objective: This study aims to develop a contrast-free, high-sensitivity ultrasound method, denoted as Radon transform-based flow measurement (R-Flow), for in vivo mapping of microvascular flow vectors and for establishing R-Flow-derived vector-field metrics to noninvasively quantify microcirculatory patterns in liver cirrhosis. Impact Statement: R-Flow enables robust, contrast-free imaging of microvascular dynamics and demonstrates translational feasibility in the human liver. Its direction-aware indices offer pilot in vivo quantification of flow redistribution and remodeling, providing unique insights into hepatic flow dynamics. Introduction: Microvascular dysfunction is a hallmark of many diseases, yet noninvasive visualization and quantitative assessment of abnormal microcirculation remain limited. Methods: R-Flow leverages Radon transform to decode red blood cell dynamics from the spatiotemporal domain of ultrasound flow signals, reconstructing velocity vectors at microvascular scale. From these vector maps, unique direction-aware indices are further derived to characterize flow distribution and heterogeneity. Results: Validated across simulations, phantoms, and in vivo studies, R-Flow provides robust velocity estimation across a wide range (1 to 60 mm/s). Notably, it enables high-sensitivity microvascular flow vector mapping of human liver, showing strong agreement with references ( r > 0.9). In a rat model, these direction-aware indices revealed a shift from healthy multipath perfusion in control livers to directionally biased vascular pattern in cirrhotic livers, demonstrating significant correlation with pathological indicators. Conclusion: R-Flow enables noninvasive, contrast-free mapping of microvascular blood flow velocity and offers a promising approach for high-resolution assessment of microvascular flow characteristics.