Simplifying Medical Ultrasound

.- Image Acquisition, Synthesis and Enhancement.
.- Unsupervised Physics-Inspired Shear Wave Speed Estimation in Ultrasound Elastography.
.- Simplifying Prostate Elastography Using Micro-Ultrasound and Transfer Function Imaging.
.- Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer.
.- PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement.
.- Tracking, Registration and Image-guided Interventions.
.- PIPsUS: Self-Supervised Point Tracking in Ultrasound.
.- Structure-aware World Model for Probe Guidance via Large-scale Selfsupervised Pre-train.
.- An Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy.
.- Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound.
.- Automatic facial axes standardization of 3D fetal ultrasound images.
.- Segmentation.
.- C-TRUS: A Novel Dataset and Initial Benchmark For Colon Wall Segmentation in Transabdominal Ultrasound.
.- Label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets With Domain Shift and Partial Labelling.
.- Introducing Anatomical Constraints in Mitral Annulus Segmentation in Transesophageal Echocardiography.
.- Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound Images.
.- Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net.
.- Classification and Detection.
.- Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography.
.- Masked autoencoders for medical ultrasound videos using ROI-aware masking.
.- Uncertainty-based Multi-modal Learning for Myocardial Infarction Diagnosis using Echocardiography and Electrocardiograms.
.- Fetal Ultrasound Video Representation Learning using Contrastive Rubik's Cube Recovery.
.- LoRIS - Weakly-supervised Anomaly Detection for Ultrasound Images.
.- Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models.
.- Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound.