27 citations · 86 across the 9 of their papers we have counts for
9 papers
QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge
Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
Framing image registration as a landmark detection problem for label-noise-aware task representation (HitR)
Diana Waldmannstetter, Ivan Ezhov, Benedikt Wiestler +16
Accurate image registration is pivotal in biomedical image analysis, where selecting suitable registration algorithms demands careful consideration. While numerous algorithms are a…
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Florian Kofler, Felix Meissen, Felix Steinbauer +103
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
Diana Waldmannstetter, Benedikt Wiestler, Julian Schwarting +11
Even though simultaneous optimization of similarity metrics is a standard procedure in the field of semantic segmentation, surprisingly, this is much less established for image reg…
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Bhakti Baheti, Satrajit Chakrabarty, Hamed Akbari +70
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been progress in developing gene…
Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
Ivan Ezhov, Kevin Scibilia, Katharina Franitza +12
Current treatment planning of patients diagnosed with a brain tumor, such as glioma, could significantly benefit by accessing the spatial distribution of tumor cell concentration.…
Deep Reinforcement Learning for Organ Localization in CT
Fernando Navarro, Anjany Sekuboyina, Diana Waldmannstetter +3
Robust localization of organs in computed tomography scans is a constant pre-processing requirement for organ-specific image retrieval, radiotherapy planning, and interventional im…
Deep learning-based parameter mapping for joint relaxation and diffusion tensor MR Fingerprinting
Carolin M. Pirkl, Pedro A. Gómez, Ilona Lipp +13
Magnetic Resonance Fingerprinting (MRF) enables the simultaneous quantification of multiple properties of biological tissues. It relies on a pseudo-random acquisition and the match…