Publications (8)
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…
On The Usage Of Average Hausdorff Distance For Segmentation Performance Assessment: Hidden Bias When Used For Ranking
Orhun Utku Aydin, Abdel Aziz Taha, Adam Hilbert +5
Average Hausdorff Distance (AVD) is a widely used performance measure to calculate the distance between two point sets. In medical image segmentation, AVD is used to compare ground…
Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review
Luis M. Lopez-Ramos, Florian Leiser, Aditya Rastogi +6
The joint implementation of federated learning (FL) and explainable artificial intelligence (XAI) could allow training models from distributed data and explaining their inner worki…
HemExp: Clinically-Guided Latent Diffusion for Modeling Hematoma Expansion
Orhun Utku Aydin, Satoru Tanioka, Tzu I Chuang +7
Hematoma expansion (HE) after spontaneous intracerebral hemorrhage (ICH) is a major determinant of acute triage and treatment decisions in neurosurgical care. However, most existin…
From Single-Hospital to Multi-Centre Applications: Enhancing the Generalisability of Deep Learning Models for Adverse Event Prediction in the ICU
Patrick Rockenschaub, Adam Hilbert, Tabea Kossen +3
Deep learning (DL) can aid doctors in detecting worsening patient states early, affording them time to react and prevent bad outcomes. While DL-based early warning models usually w…
RELICT: A Replica Detection Framework for Medical Image Generation
Orhun Utku Aydin, Alexander Koch, Adam Hilbert +5
Despite the potential of synthetic medical data for augmenting and improving the generalizability of deep learning models, memorization in generative models can lead to unintended…