4 papers · 1 filter
EchoVLM: Measurement-Grounded Multimodal Learning for Echocardiography
Yuheng Li, Yue Zhang, Abdoul Aziz Amadou +5
Echocardiography is the most widely used imaging modality in cardiology, yet its interpretation remains labor-intensive and inherently multimodal, requiring view recognition, quant…
A Novel Tracking Framework for Devices in X-ray Leveraging Supplementary Cue-Driven Self-Supervised Features
Saahil Islam, Venkatesh N. Murthy, Dominik Neumann +5
To restore proper blood flow in blocked coronary arteries via angioplasty procedure, accurate placement of devices such as catheters, balloons, and stents under live fluoroscopy or…
Self-Supervised Learning for Interventional Image Analytics: Towards Robust Device Trackers
Saahil Islam, Venkatesh N. Murthy, Dominik Neumann +5
An accurate detection and tracking of devices such as guiding catheters in live X-ray image acquisitions is an essential prerequisite for endovascular cardiac interventions. This i…
Goal-conditioned reinforcement learning for ultrasound navigation guidance
Abdoul Aziz Amadou, Vivek Singh, Florin C. Ghesu +7
Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures. However, using it effectively requires extensive training du…