no code implementations • 7 Aug 2024 • 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
Our experiments on a real-world clinical dataset show the potential of using unsupervised methods for fetal brain anomaly detection.
1 code implementation • 14 May 2024 • Tiantian Zhang, Manxi Lin, Hongda Guo, Xiaofan Zhang, Ka Fung Peter Chiu, Aasa Feragen, Qi Dou
In the second stage, we translate PICG for guiding instructions from the model to generate PICG-guided image features.
no code implementations • 14 Apr 2024 • Diandian Guo, Manxi Lin, Jialun Pei, He Tang, Yueming Jin, Pheng-Ann Heng
A comprehensive understanding of surgical scenes allows for monitoring of the surgical process, reducing the occurrence of accidents and enhancing efficiency for medical professionals.
no code implementations • 22 Mar 2024 • Chun Kit Wong, Mary Ngo, Manxi Lin, Zahra Bashir, Amihai Heen, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen
Despite the rapid development of AI models in medical image analysis, their validation in real-world clinical settings remains limited.
no code implementations • 13 Mar 2024 • Paraskevas Pegios, Manxi Lin, Nina Weng, Morten Bo Søndergaard Svendsen, Zahra Bashir, Siavash Bigdeli, Anders Nymark Christensen, Martin Tolsgaard, Aasa Feragen
Obstetric ultrasound image quality is crucial for accurate diagnosis and monitoring of fetal health.
1 code implementation • 11 Mar 2024 • Manxi Lin, Nina Weng, Kamil Mikolaj, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Tolsgaard, Anders Nymark Christensen, Aasa Feragen
Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training set.
1 code implementation • 22 Feb 2024 • Jialun Pei, Diandian Guo, Jingyang Zhang, Manxi Lin, Yueming Jin, Pheng-Ann Heng
In this study, we introduce a novel single-stage bi-modal transformer framework for SGG in the OR, termed S^2Former-OR, aimed to complementally leverage multi-view 2D scenes and 3D point clouds for SGG in an end-to-end manner.
no code implementations • 13 Feb 2024 • 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
We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements.
no code implementations • 11 Apr 2023 • Chun Kit Wong, Manxi Lin, Alberto Raheli, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Aasa Feragen, Anders Nymark Christensen
Examination of the umbilical artery with Doppler ultrasonography is performed to investigate blood supply to the fetus through the umbilical cord, which is vital for the monitoring of fetal health.
no code implementations • 24 Mar 2023 • Kamil Mikolaj, Manxi Lin, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Tolsgaard, Anders Nymark, Aasa Feragen
In order to utilize the vast amounts of data available in these databases, we develop and validate a series of methods for minimizing the confounding effects of embedded text and calipers on deep learning algorithms designed for ultrasound, using standard plane classification as a test case.
no code implementations • 19 Nov 2022 • Manxi Lin, Aasa Feragen, Zahra Bashir, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen
Concept bottleneck models (CBMs) include a bottleneck of human-interpretable concepts providing explainability and intervention during inference by correcting the predicted, intermediate concepts.
no code implementations • 23 May 2022 • Manxi Lin, Zahra Bashir, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen
We conduct experiments on a challenging multi-class ultrasound scan segmentation dataset as well as a well-known retinal imaging dataset.
1 code implementation • 29 Nov 2021 • Manxi Lin, Aasa Feragen
Standard spatial convolutions assume input data with a regular neighborhood structure.