8 papers
Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge
Yuan Jin, Antonio Pepe, Gian Marco Melito +36
The automated analysis of the aortic vessel tree (AVT) from computed tomography angiography (CTA) holds immense clinical potential, but its development has been impeded by a lack o…
Robust Photo-Realistic Hand Gesture Generation: from Single View to Multiple View
Qifan Fu, Xu Chen, Muhammad Asad +3
High-fidelity hand gesture generation represents a significant challenge in human-centric generation tasks. Existing methods typically employ a single-view mesh-rendered image prio…
HanDrawer: Leveraging Spatial Information to Render Realistic Hands Using a Conditional Diffusion Model in Single Stage
Qifan Fu, Xu Chen, Muhammad Asad +3
Although diffusion methods excel in text-to-image generation, generating accurate hand gestures remains a major challenge, resulting in severe artifacts, such as incorrect number o…
Compositional Segmentation of Cardiac Images Leveraging Metadata
Abbas Khan, Muhammad Asad, Martin Benning +2
Cardiac image segmentation is essential for automated cardiac function assessment and monitoring of changes in cardiac structures over time. Inspired by coarse-to-fine approaches i…
Adaptive Multi-Modal Control of Digital Human Hand Synthesis Using a Region-Aware Cycle Loss
Qifan Fu, Xiaohang Yang, Muhammad Asad +3
Diffusion models have shown their remarkable ability to synthesize images, including the generation of humans in specific poses. However, current models face challenges in adequate…
CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation
Abbas Khan, Muhammad Asad, Martin Benning +2
Convolutional Neural Networks (CNNs) and Transformer-based self-attention models have become the standard for medical image segmentation. This paper demonstrates that convolution a…
Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors
Abbas Khan, Muhammad Asad, Martin Benning +2
We propose a novel multi-stage trans-dimensional architecture for multi-view cardiac image segmentation. Our method exploits the relationship between long-axis (2D) and short-axis…
Crop and Couple: cardiac image segmentation using interlinked specialist networks
Abbas Khan, Muhammad Asad, Martin Benning +2
Diagnosis of cardiovascular disease using automated methods often relies on the critical task of cardiac image segmentation. We propose a novel strategy that performs segmentation…