Adaptive Query Prompting for Multi-Domain Landmark Detection

arXiv:2404.01194v1 Announce Type: new
Abstract: Medical landmark detection is crucial in various medical imaging modalities and procedures. Although deep learning-based methods have achieve promising performance, they are mostly designed for specific anatomical regions or tasks. In this work, we propose a universal model for multi-domain landmark detection by leveraging transformer architecture and developing a prompting component, named as Adaptive Query Prompting (AQP). Instead of embedding additional modules in the backbone network, we design a separate module to generate prompts that …

abstract architecture arxiv cs.cv deep learning detection domain imaging landmark medical medical imaging performance prompting query tasks transformer transformer architecture type universal universal model work