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ASMUS@MICCAI 2024: Marrakesh, Morocco
- Alberto Gómez, Bishesh Khanal, Andrew P. King, Ana I. L. Namburete:
Simplifying Medical Ultrasound - 5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15186, Springer 2025, ISBN 978-3-031-73646-9
Image Acquisition, Synthesis and Enhancement
- Ali Kafaei Zad Tehrani, E. G. Sunethra Dayavansha, Yuyang Gu, Ion Candel, Michael Wang, Rimon Tadross, Yiming Xiao, Hassan Rivaz, Kai Thomenius, Anthony E. Samir:
Unsupervised Physics-Inspired Shear Wave Speed Estimation in Ultrasound Elastography. 3-13 - Reid Vassallo, Tajwar Abrar Aleef, Vedanth Desaigoudar, Qi Zeng, David Black, Brian Wodlinger, Miles Mannas, Peter C. Black, Septimiu E. Salcudean:
Simplifying Prostate Elastography Using Micro-ultrasound and Transfer Function Imaging. 14-23 - Mohammad R. Salmanpour, Amin Mousavi, Yixi Xu, William B. Weeks, Ilker Hacihaliloglu:
Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer. 24-34 - Felix Duelmer, Walter Simson, Mohammad Farid Azampour, Magdalena Wysocki, Angelos Karlas, Nassir Navab:
PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement. 35-44
Tracking, Registration and Image-guided Interventions
- Wanwen Chen, Adam Schmidt, Eitan Prisman, Septimiu E. Salcudean:
PIPsUS: Self-supervised Point Tracking in Ultrasound. 47-57 - Haojun Jiang, Meng Li, Zhenguo Sun, Ning Jia, Yu Sun, Shaqi Luo, Shiji Song, Gao Huang:
Structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-train. 58-67 - Étienne Léger, Niki Najafi, Houssem-Eddine Gueziri, D. Louis Collins, Marta Kersten-Oertel:
An Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy. 68-77 - Hassan Rasheed, Reuben Dorent, Maximilian Fehrentz, Tina Kapur, William M. Wells III, Alexandra J. Golby, Sarah F. Frisken, Julia A. Schnabel, Nazim Haouchine:
Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound. 78-87 - Antònia Alomar, Ricardo Rubio, Laura Salort, Gerard Albaiges, Antoni Payà, Gemma Piella, Federico Sukno:
Automatic Facial Axes Standardization of 3D Fetal Ultrasound Images. 88-98
Segmentation
- Ramona Leenings, Maximilian Konowski, Nils R. Winter, Jan Ernsting, Lukas Fisch, Carlotta B. C. Barkhau, Udo Dannlowski, Andreas Lügering, Xiaoyi Jiang, Tim Hahn:
C-TRUS: A Novel Dataset and Initial Benchmark for Colon Wall Segmentation in Transabdominal Ultrasound. 101-111 - Iman Islam, Esther Puyol-Antón, Bram Ruijsink, Andrew J. Reader, Andrew P. King:
Label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets with Domain Shift and Partial Labelling. 112-121 - Børge Solli Andreassen, Sarina Thomas, Anne H. Schistad Solberg, Eigil Samset, David Völgyes:
Introducing Anatomical Constraints in Mitral Annulus Segmentation in Transesophageal Echocardiography. 122-131 - Hao Li, Baris U. Oguz, Gabriel Arenas, Xing Yao, Jiacheng Wang, Alison M. Pouch, Brett C. Byram, Nadav Schwartz, Ipek Oguz:
Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound Images. 132-142 - Rohini Banerjee, Cecilia G. Morales, Artur Dubrawski:
Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net. 143-153
Classification and Detection
- Kit Mills Bransby, Woo-Jin Cho Kim, Jorge Oliveira, Alexander Thorley, Arian Beqiri, Alberto Gómez, Agisilaos Chartsias:
Multi-site Class-Incremental Learning with Weighted Experts in Echocardiography. 157-166 - Ádám Szijártó, Bálint Magyar, Thomas Á. Szeier, Máté Tolvaj, Alexandra Fábián, Bálint Károly Lakatos, Zsuzsanna Ladányi, Zsolt Bagyura, Béla Merkely, Attila Kovács, Márton Tokodi:
Masked Autoencoders for Medical Ultrasound Videos Using ROI-Aware Masking. 167-176 - Yingyu Yang, Marie Rocher, Pamela Moceri, Maxime Sermesant:
Uncertainty-Based Multi-modal Learning for Myocardial Infarction Diagnosis Using Echocardiography and Electrocardiograms. 177-186 - Kangning Zhang, Jianbo Jiao, J. Alison Noble:
Fetal Ultrasound Video Representation Learning Using Contrastive Rubik's Cube Recovery. 187-197 - Marco Colussi, Dragan Ahmetovic, Gabriele Civitarese, Claudio Bettini, Aiman Solyman, Roberta Gualtierotti, Flora Peyvandi, Sergio Mascetti:
LoRIS - Weakly-Supervised Anomaly Detection for Ultrasound Images. 198-208 - Markus Ditlev Sjøgren Olsen, Jakob Ambsdorf, Manxi Lin, Caroline Taksøe-Vester, Morten Bo Søndergaard Svendsen, Anders Nymark Christensen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Aasa Feragen, Paraskevas Pegios:
Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models. 209-219 - Hanna Mykula, Lisa Gasser, Silvia Lobmaier, Julia A. Schnabel, Veronika A. M. Zimmer, Cosmin I. Bercea:
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound. 220-230
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