36 papers
MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models
Lisa K. Fischer, Mykhailo Riabets, Daniel Rueckert +3
Large-scale multi-modal MRI datasets impose substantial storage and I/O costs, limiting the training of 3D generative models on commodity infrastructure. While lossy compression is…
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…
Optimizing Rank for High-Fidelity Implicit Neural Representations
Julian McGinnis, Florian A. Hölzl, Suprosanna Shit +6
Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-frequency content. This has directed…
Inpainting physics: self-supervised learning for context-driven fluid simulation
Jonas Weidner, Yeray Martin-Ruisanchez, Daniel Rueckert +2
Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such as geometry and boundary co…
Multimodal Graph-based Classification of Esophageal Motility Disorders
Alexander Geiger, Lars Wagner, Daniel Rueckert +3
Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variability in clinical interpreta…
RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
Chengzhi Shen, Weixiang Shen, Tobias Susetzky +7
Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states under time pressure, undersco…