Martin Grønnebæk Tolsgaard

According to our database, Martin Grønnebæk Tolsgaard authored at least 16 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound.

Jakob Ambsdorf, Asbjørn Munk, Sebastian Nørgaard Llambias, Anders Nymark Christensen, Kamil Wojciech Mikolaj, Randall Balestriero, Martin Grønnebæk Tolsgaard, Aasa Feragen, Mads Nielsen

CoRR, June, 2025

Clinical needs and preferences for AI-based explanations in clinical simulation training.

Naja Kathrine Kollerup, Stine S. Johansen, Martin Grønnebæk Tolsgaard, Mikkel Lønborg Friis, Mikael B. Skov, Niels van Berkel

Behav. Inf. Technol., March, 2025

Predicting abnormal fetal growth using deep learning.

Kamil Wojciech Mikolaj, Anders Nymark Christensen, Caroline Taksøe-Vester, Aasa Feragen, Olav Bjørn Petersen, Manxi Lin, Mads Nielsen, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard

npj Digit. Medicine, 2025

Determining Fetal Orientations From Blind Sweep Ultrasound Video.

Jakub Maciej Wisniewski, Anders Nymark Christensen, Mary Ngo, Martin Grønnebæk Tolsgaard, Chun Kit Wong

Proceedings of the Image Analysis - 23rd Scandinavian Conference, 2025

2024

Deployment of Deep Learning Model in Real World Clinical Setting: A Case Study in Obstetric Ultrasound.

Chun Kit Wong, Mary Ngo, Manxi Lin, Zahra Bashir, Amihai Heen, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

CoRR, 2024

Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment.

Paraskevas Pegios, Manxi Lin, Nina Weng, Morten Bo Søndergaard Svendsen, Zahra Bashir, Siavash Arjomand Bigdeli, Anders Nymark Christensen, Martin Grønnebæk Tolsgaard, Aasa Feragen

CoRR, 2024

Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models.

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

Proceedings of the Simplifying Medical Ultrasound - 5th International Workshop, 2024

Shortcut Learning in Medical Image Segmentation.

Manxi Lin, Nina Weng, Kamil Wojciech Mikolaj, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Learning Semantic Image Quality for Fetal Ultrasound from Noisy Ranking Annotation.

Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer, Zahra Bashir, Chun Kit Wong, Paraskevas Pegios, Alberto Raheli, Morten Bo Søndergaard Svendsen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023

Removing confounding information from fetal ultrasound images.

Kamil Wojciech Mikolaj, Manxi Lin, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

CoRR, 2023

An Automatic Guidance and Quality Assessment System for Doppler Imaging of Umbilical Artery.

Chun Kit Wong, Manxi Lin, Alberto Raheli, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Aasa Feragen, Anders Nymark Christensen

Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

Leveraging Shape and Spatial Information for Spontaneous Preterm Birth Prediction.

Paraskevas Pegios, Emilie Pi Fogtmann Sejer, Manxi Lin, Zahra Bashir, Morten Bo Søndergaard Svendsen, Mads Nielsen, Eike Petersen, Anders Nymark Christensen, Martin Grønnebæk Tolsgaard, Aasa Feragen

Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation.

Manxi Lin, Kilian Zepf, Anders Nymark Christensen, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Aasa Feragen

Proceedings of the Information Processing in Medical Imaging, 2023

2022

I saw, I conceived, I concluded: Progressive Concepts as Bottlenecks.

Manxi Lin, Aasa Feragen, Zahra Bashir, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen

CoRR, 2022

Generalisability of deep learning models in low-resource imaging settings: A fetal ultrasound study in 5 African countries.

Carla Sendra-Balcells, Víctor M. Campello, Jordina Torrents-Barrena, Yahya Ali Ahmed, Mustafa A. Elattar, Benard Ohene Botwe, Pempho Nyangulu, William Stones, Mohammed Ammar, Lamya Nawal Benamer, Harriet Nalubega Kisembo, Senai Goitom Sereke, Sikolia Z. Wanyonyi, Marleen Temmerman, Kamil Wojciech Mikolaj, Martin Grønnebæk Tolsgaard, Karim Lekadir

CoRR, 2022

DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation.

Manxi Lin, Zahra Bashir, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

CoRR, 2022