4 citations · 11 across the 7 of their papers we have counts for
9 papers
SWoMo: Neuro-Symbolic World Model for Cataract Surgery Simulation
Ssharvien Kumar Sivakumar, Akwele Johnson, Anirudh Dhingra +3
Realistic surgical simulation plays a crucial role in training novice surgeons and in the development of autonomous agents. World models can scale such simulation environments to r…
VolDiT: Controllable Volumetric Medical Image Synthesis with Diffusion Transformers
Marvin Seyfarth, Salman Ul Hassan Dar, Yannik Frisch +4
Diffusion models have become a leading approach for high-fidelity medical image synthesis. However, most existing methods for 3D medical image generation rely on convolutional U-Ne…
SG2VID: Scene Graphs Enable Fine-Grained Control for Video Synthesis
Ssharvien Kumar Sivakumar, Yannik Frisch, Ghazal Ghazaei +1
Surgical simulation plays a pivotal role in training novice surgeons, accelerating their learning curve and reducing intra-operative errors. However, conventional simulation tools…
SASVi -- Segment Any Surgical Video
Ssharvien Kumar Sivakumar, Yannik Frisch, Amin Ranem +1
Purpose: Foundation models, trained on multitudes of public datasets, often require additional fine-tuning or re-prompting mechanisms to be applied to visually distinct target doma…
SurGrID: Controllable Surgical Simulation via Scene Graph to Image Diffusion
Yannik Frisch, Ssharvien Kumar Sivakumar, Çağhan Köksal +5
Surgical simulation offers a promising addition to conventional surgical training. However, available simulation tools lack photorealism and rely on hardcoded behaviour. Denoising…
GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentation
Yannik Frisch, Christina Bornberg, Moritz Fuchs +1
Augmentation by generative modelling yields a promising alternative to the accumulation of surgical data, where ethical, organisational and regulatory aspects must be considered. Y…