65 citations · 79 across the 4 of their papers we have counts for
4 papers
Robustness of breast lesion segmentation under MRI undersampling improves with k-space-aware deep learning
Lukas T. Rotkopf, Marco Schlimbach, Julius C. Holzschuh +3
Purpose: To assess whether breast lesion segmentation can be learned directly from acquired MRI k-space, and whether doing so improves robustness when data are accelerated or noisy…
Mitigating False Predictions In Unreasonable Body Regions
Constantin Ulrich, Catherine Knobloch, Julius C. Holzschuh +7
Despite considerable strides in developing deep learning models for 3D medical image segmentation, the challenge of effectively generalizing across diverse image distributions pers…
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…
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…