127 citations · 221 across the 6 of their papers we have counts for
3 papers · 1 filter
atTRACTive: Semi-automatic white matter tract segmentation using active learning
Robin Peretzke, Klaus Maier-Hein, Jonas Bohn +6
Accurately identifying white matter tracts in medical images is essential for various applications, including surgery planning and tract-specific analysis. Supervised machine learn…
SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model
Saikat Roy, Tassilo Wald, Gregor Koehler +5
Foundation models have taken over natural language processing and image generation domains due to the flexibility of prompting. With the recent introduction of the Segment Anything…
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
Saikat Roy, Gregor Koehler, Constantin Ulrich +5
There has been exploding interest in embracing Transformer-based architectures for medical image segmentation. However, the lack of large-scale annotated medical datasets make achi…