Digital Twin for Healthcare

Personalized 3D Myocardial Infarct Geometry Reconstruction from Cine MRI with Explicit Cardiac Motion Modeling.- Microvascular Retinal Digital Twins from Non-Invasive Clinical Images.- Validating Digital Twins with Tactile-Visual Liver Phantoms for Robot-Assisted Surgical Workflows.- A Real-Time Digital Twin for Type 1 Diabetes using Simulation-Based Inference.- Retrospective Evaluation of a Patient-Specific Liver Digital Twin to Predict Thermal Ablation Outcomes in HCC.- Acoustic Simulation with Deep Learning for Low-intensity Transcranial Focused Ultrasound Digital Twins.- Towards Digital Twin of RF Ablation: Real-Time Prediction of Time-Dependent Thermal Effects Using Transformer.- Finite-Element Electrophysiological Modeling of Human Uterine Smooth Muscle Using a Reduced Tong Model.- TF-TransUNet1D: Time-Frequency Guided Transformer U-Net for Robust ECG De-noising in Digital Twin.- DeformMLP: Effective Deformation Prediction for Breast Cancer Using Graph To-pology-Assisted MLPs.- Rule-based Key-Point Extraction for MR-Guided Biomechanical Digital Twins of the Spine.- Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Repre-sentation.- Personalized 4D Whole Heart Geometry Reconstruction from Cine MRI for Cardiac Digital Twins.- Secure Medical Digital Twins: A Use-Case Driven Approach.- Explainable Prediction of Recurrence After Prostate Cancer Radiotherapy Using in Silico Digital Twin Model and Machine Learning.