5 papers
Coarse to Fine: Iterative Adversarial Neural Cellular Automata for Medical Image Synthesis
Anh Thi Luu, Nick Lemke, Anirban Mukhopadhyay
Large-scale, publicly available datasets have driven advances in deep learning, but privacy and legal restrictions often limit data sharing in medical imaging. Synthetic data gener…
Sterilizable Scene Graph Generation for Operating Rooms
Nick Lemke, Ssharvien Kumar Sivakumar, Antoine P. Sanner +4
Scene graph generation from surgical video enables a holistic and structured understanding of surgical scenes by modeling objects and their semantic relationships. Despite recent a…
OctreeNCA: Single-Pass 184 MP Segmentation on Consumer Hardware
Nick Lemke, John Kalkhof, Niklas Babendererde +1
Medical applications demand segmentation of large inputs, like prostate MRIs, pathology slices, or videos of surgery. These inputs should ideally be inferred at once to provide the…
Equitable Federated Learning with NCA
Nick Lemke, Mirko Konstantin, Henry John Krumb +3
Federated Learning (FL) is enabling collaborative model training across institutions without sharing sensitive patient data. This approach is particularly valuable in low- and midd…
Distribution-Aware Replay for Continual MRI Segmentation
Nick Lemke, Camila González, Anirban Mukhopadhyay +1
Medical image distributions shift constantly due to changes in patient population and discrepancies in image acquisition. These distribution changes result in performance deteriora…