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Netherlands Cancer Institute, Radboud University Medical Center
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Interactive lesion segmentation can now adaptively refine predictions in real-time, significantly improving accuracy in heterogeneous PET/CT datasets.
ClinRAG-GRAPH achieves impressive pCR prediction accuracy while ensuring interpretability and robustness against imaging biases across multiple centers.
Top algorithms in the HECKTOR 2025 challenge achieved impressive segmentation and survival prediction metrics, showcasing the power of multimodal imaging in oncology.
Synthesized breast MRIs can now better mimic real-world lesion complexity thanks to a diffusion model that explicitly handles multi-scale features and heterogeneous enhancement.
Breast cancer risk prediction from MRI just got a whole lot faster and more interpretable, thanks to a novel 2.5D approach that beats both 2D and 3D models.
