14 citations · 15 across the 6 of their papers we have counts for
6 papers
Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis
Sven Lüpke, Yousef Yeganeh, Ehsan Adeli +2
Recent advances in generative models for medical imaging have shown promise in representing multiple modalities. However, the variability in modality availability across datasets l…
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder
Matan Atad, David Schinz, Hendrik Moeller +6
Counterfactual explanations (CEs) aim to enhance the interpretability of machine learning models by illustrating how alterations in input features would affect the resulting predic…
KLDD: Kalman Filter based Linear Deformable Diffusion Model in Retinal Image Segmentation
Zhihao Zhao, Yinzheng Zhao, Junjie Yang +3
AI-based vascular segmentation is becoming increasingly common in enhancing the screening and treatment of ophthalmic diseases. Deep learning structures based on U-Net have achieve…
Intraoperative Registration by Cross-Modal Inverse Neural Rendering
Maximilian Fehrentz, Mohammad Farid Azampour, Reuben Dorent +7
We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural…
SURGIVID: Annotation-Efficient Surgical Video Object Discovery
Çağhan Köksal, Ghazal Ghazaei, Nassir Navab
Surgical scenes convey crucial information about the quality of surgery. Pixel-wise localization of tools and anatomical structures is the first task towards deeper surgical analys…
MAGDA: Multi-agent guideline-driven diagnostic assistance
David Bani-Harouni, Nassir Navab, Matthias Keicher
In emergency departments, rural hospitals, or clinics in less developed regions, clinicians often lack fast image analysis by trained radiologists, which can have a detrimental eff…