Transformers pay attention to convolutions leveraging emerging properties of ViTs by dual attention-image network
Although purely transformer-based architectures pretrained on large datasets are introduced
as foundation models for general computer vision tasks, hybrid models that incorporate …
as foundation models for general computer vision tasks, hybrid models that incorporate …
Scenegenie: Scene graph guided diffusion models for image synthesis
Text-conditioned image generation has made significant progress in recent years with
generative adversarial networks and more recently, diffusion models. While diffusion models …
generative adversarial networks and more recently, diffusion models. While diffusion models …
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET
Over the past years, pseudo-healthy reconstruction for unsupervised anomaly detection has
gained in popularity. This approach has the great advantage of not requiring tedious pixel …
gained in popularity. This approach has the great advantage of not requiring tedious pixel …
VISAGE: Video Synthesis using Action Graphs for Surgery
Y Yeganeh, R Lazuardi, A Shamseddin, E Dari… - arXiv preprint arXiv …, 2024 - arxiv.org
Surgical data science (SDS) is a field that analyzes patient data before, during, and after
surgery to improve surgical outcomes and skills. However, surgical data is scarce …
surgery to improve surgical outcomes and skills. However, surgical data is scarce …
Anatomy-Aware Masking for Inpainting in Medical Imaging
Inpainting has recently been employed as a successful deep-learning technique for
unsupervised model discovery in medical image analysis by taking advantage of the strong …
unsupervised model discovery in medical image analysis by taking advantage of the strong …