E-grāmata: Simplifying Medical Ultrasound: 5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

.- 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 Rubiks
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.