13 citations · 49 across the 13 of their papers we have counts for
15 papers
CardioDiT: Latent Diffusion Transformers for 4D Cardiac MRI Synthesis
Marvin Seyfarth, Sarah Kaye Müller, Arman Ghanaat +7
Latent diffusion models (LDMs) have recently achieved strong performance in 3D medical image synthesis. However, modalities like cine cardiac MRI (CMR), representing a temporally s…
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…
Latent Pollution Model: The Hidden Carbon Footprint in 3D Image Synthesis
Marvin Seyfarth, Salman Ul Hassan Dar, Sandy Engelhardt
Contemporary developments in generative AI are rapidly transforming the field of medical AI. These developments have been predominantly driven by the availability of large datasets…
Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic Data
Salman Ul Hassan Dar, Marvin Seyfarth, Isabelle Ayx +11
AI models present a wide range of applications in the field of medicine. However, achieving optimal performance requires access to extensive healthcare data, which is often not rea…
Investigating Data Memorization in 3D Latent Diffusion Models for Medical Image Synthesis
Salman Ul Hassan Dar, Arman Ghanaat, Jannik Kahmann +4
Generative latent diffusion models have been established as state-of-the-art in data generation. One promising application is generation of realistic synthetic medical imaging data…
BolT: Fused Window Transformers for fMRI Time Series Analysis
Hasan Atakan Bedel, Irmak Şıvgın, Onat Dalmaz +2
Deep-learning models have enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for contextual…