5 papers
Learning Human Motion with Temporally Conditional Mamba
Quang Nguyen, Tri Le, Baoru Huang +4
Learning human motion based on a time-dependent input signal presents a challenging yet impactful task with various applications. The goal of this task is to generate or estimate h…
FedEFM: Federated Endovascular Foundation Model with Unseen Data
Tuong Do, Nghia Vu, Tudor Jianu +7
In endovascular surgery, the precise identification of catheters and guidewires in X-ray images is essential for reducing intervention risks. However, accurately segmenting cathete…
SplineFormer: An Explainable Transformer-Based Approach for Autonomous Endovascular Navigation
Tudor Jianu, Shayan Doust, Mengyun Li +8
Endovascular navigation is a crucial aspect of minimally invasive procedures, where precise control of curvilinear instruments like guidewires is critical for successful interventi…
Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications
Nghia Nguyen, Minh Nhat Vu, Tung D. Ta +4
Vision language models have played a key role in extracting meaningful features for various robotic applications. Among these, Contrastive Language-Image Pretraining (CLIP) is wide…
CathAction: A Benchmark for Endovascular Intervention Understanding
Baoru Huang, Tuan Vo, Chayun Kongtongvattana +35
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are of…