activity
20232026
most citedGenerative AI for Medical Imaging: extending the MONAI Framework

41 citations · 41 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

SceneForge: Structured World Supervision from 3D Interventions

Jizhizi Li, Jiayang Ao, Danny Wicks +1

Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints, and scene-level interventions. However, such supervision is difficult to obtain…

cs.CV2025

A Practical Investigation of Spatially-Controlled Image Generation with Transformers

Guoxuan Xia, Harleen Hanspal, Petru-Daniel Tudosiu +2

Enabling image generation models to be spatially controlled is an important area of research, empowering users to better generate images according to their own fine-grained specifi…

cs.CL2025

Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities

Raman Dutt, Harleen Hanspal, Guoxuan Xia +5

In this work, we undertake the challenge of augmenting the existing generative capabilities of pre-trained text-only large language models (LLMs) with multi-modal generation capabi…

cs.CV2024

Generating Compositional Scenes via Text-to-image RGBA Instance Generation

Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang +2

Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditio…

cs.CV2024

MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation

Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang +5

Text-to-image generation has achieved astonishing results, yet precise spatial controllability and prompt fidelity remain highly challenging. This limitation is typically addressed…

cs.CV2023

Optimisation-Based Multi-Modal Semantic Image Editing

Bowen Li, Yongxin Yang, Steven McDonagh +3

Image editing affords increased control over the aesthetics and content of generated images. Pre-existing works focus predominantly on text-based instructions to achieve desired im…

eess.IV2023

InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model

Jueqi Wang, Jacob Levman, Walter Hugo Lopez Pinaya +3

High-resolution (HR) MRI scans obtained from research-grade medical centers provide precise information about imaged tissues. However, routine clinical MRI scans are typically in l…

eess.IV2023★ 41 cited

Generative AI for Medical Imaging: extending the MONAI Framework

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot +21

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to he…

cs.CV2023

Unsupervised 3D out-of-distribution detection with latent diffusion models

Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright +8

Methods for out-of-distribution (OOD) detection that scale to 3D data are crucial components of any real-world clinical deep learning system. Classic denoising diffusion probabilis…