1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Cycle-Consistent Graph Surrogate for Full-Cycle Left Ventricular Myocardial Biomechanics
Siyu Mu, Wei Xuan Chan, Choon Hwai Yap
Image-based patient-specific simulation of left ventricular (LV) mechanics is valuable for understanding cardiac function and supporting clinical intervention planning, but convent…
HeartUnloadNet: A Weakly-Supervised Cycle-Consistent Graph Network for Predicting Unloaded Cardiac Geometry from Diastolic States
Siyu Mu, Wei Xuan Chan, Choon Hwai Yap
The unloaded cardiac geometry (i.e., the state of the heart devoid of luminal pressure) serves as a valuable zero-stress and zero-strain reference and is critical for personalized…
IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Siyu Mu, Wei Xuan Chan, Choon Hwai Yap
Elucidating the biomechanical behavior of the myocardium is crucial for understanding cardiac physiology, but cannot be directly inferred from clinical imaging and typically requir…
Multiple Case Physics-Informed Neural Network for Biomedical Tube Flows
Hong Shen Wong, Wei Xuan Chan, Bing Huan Li +1
Fluid dynamics computations for tube-like geometries are important for biomedical evaluation of vascular and airway fluid dynamics. Physics-Informed Neural Networks (PINNs) have re…