6 citations · 11 across the 12 of their papers we have counts for
12 papers
Generating Reports or Repeating Templates? Measuring and Mitigating Template Collapse in 3D CT Report Generation
Tom Maye-Lasserre, Yitong Li, Bailiang Jian +3
Modern 3D medical vision-language models (VLMs) can generate fluent radiology-style text while exhibit critically low pathology detection and output diversity, collapsing to generi…
Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades
Ashkan Taghipour, Morteza Ghahremani, Zinuo Li +3
Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally…
Conditional Diffusion for 3D CT Volume Reconstruction from 2D X-rays
Martin Rath, Morteza Ghahremani, Yitong Li +3
Computed tomography (CT) provides rich 3D anatomical detail but is often constrained by high radiation exposure, substantial costs, and limited availability. Standard chest X-rays…
Disentangling Progress in Medical Image Registration: Beyond Trend-Driven Architectures towards Domain-Specific Strategies
Bailiang Jian, Jiazhen Pan, Rohit Jena +5
Medical image registration drives quantitative analysis across organs, modalities, and patient populations. Recent deep learning methods often combine low-level "trend-driven" comp…
LatentMove: Towards Complex Human Movement Video Generation
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +5
Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often s…
Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging
Yitong Li, Morteza Ghahremani, Christian Wachinger
Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is limited by severe domain shifts,…
DiaMond: Dementia Diagnosis with Multi-Modal Vision Transformers Using MRI and PET
Yitong Li, Morteza Ghahremani, Youssef Wally +1
Diagnosing dementia, particularly for Alzheimer's Disease (AD) and frontotemporal dementia (FTD), is complex due to overlapping symptoms. While magnetic resonance imaging (MRI) and…
Mamba? Catch The Hype Or Rethink What Really Helps for Image Registration
Bailiang Jian, Jiazhen Pan, Morteza Ghahremani +3
Our findings indicate that adopting "advanced" computational elements fails to significantly improve registration accuracy. Instead, well-established registration-specific designs…
Faster Image2Video Generation: A Closer Look at CLIP Image Embedding's Impact on Spatio-Temporal Cross-Attentions
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +4
This paper investigates the role of CLIP image embeddings within the Stable Video Diffusion (SVD) framework, focusing on their impact on video generation quality and computational…
Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation
Jiajun Wang, Morteza Ghahremani, Yitong Li +2
Controllable text-to-image (T2I) diffusion models have shown impressive performance in generating high-quality visual content through the incorporation of various conditions. Curre…
Box It to Bind It: Unified Layout Control and Attribute Binding in T2I Diffusion Models
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +3
While latent diffusion models (LDMs) excel at creating imaginative images, they often lack precision in semantic fidelity and spatial control over where objects are generated. To a…
RegBN: Batch Normalization of Multimodal Data with Regularization
Morteza Ghahremani, Christian Wachinger
Recent years have witnessed a surge of interest in integrating high-dimensional data captured by multisource sensors, driven by the impressive success of neural networks in the int…