5 papers
SegReg: Latent Space Regularization for Improved Medical Image Segmentation
Puru Vaish, Amin Ranem, Felix Meister +3
Medical image segmentation models are typically optimised with voxel-wise losses that constrain predictions only in the output space. This leaves latent feature representations lar…
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
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…
NCAdapt: Dynamic adaptation with domain-specific Neural Cellular Automata for continual hippocampus segmentation
Amin Ranem, John Kalkhof, Anirban Mukhopadhyay
Continual learning (CL) in medical imaging presents a unique challenge, requiring models to adapt to new domains while retaining previously acquired knowledge. We introduce NCAdapt…
NCA-Morph: Medical Image Registration with Neural Cellular Automata
Amin Ranem, John Kalkhof, Anirban Mukhopadhyay
Medical image registration is a critical process that aligns various patient scans, facilitating tasks like diagnosis, surgical planning, and tracking. Traditional optimization bas…