20 citations · 38 across the 6 of their papers we have counts for
6 papers
SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation
Ying Chen, Rami Al-Maskari, Izabela Horvath +14
Recent innovations in light sheet microscopy, paired with developments in tissue clearing techniques, enable the 3D imaging of large mammalian tissues with cellular resolution. Com…
Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
Florian Kofler, Hendrik Möller, Josef A. Buchner +18
This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. p…
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…
Approaching Peak Ground Truth
Florian Kofler, Johannes Wahle, Ivan Ezhov +15
Machine learning models are typically evaluated by computing similarity with reference annotations and trained by maximizing similarity with such. Especially in the biomedical doma…
blob loss: instance imbalance aware loss functions for semantic segmentation
Florian Kofler, Suprosanna Shit, Ivan Ezhov +14
Deep convolutional neural networks (CNN) have proven to be remarkably effective in semantic segmentation tasks. Most popular loss functions were introduced targeting improved volum…
METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy
Izabela Horvath, Johannes C. Paetzold, Oliver Schoppe +6
Novel multimodal imaging methods are capable of generating extensive, super high resolution datasets for preclinical research. Yet, a massive lack of annotations prevents the broad…