Context region discovery for automatic motion compensation in fluoroscopy

Purpose: Image-based tracking for motion compensation is an important topic in image-guided interventions, as it enables physicians to operate in a less complex space. In this paper, we propose an automatic motion compensation scheme to boost image guidence power in transcatheter aortic valve implantation (TAVI). Methods: The proposed tracking algorithm automatically discovers reliable regions that correlate strongly with the target. These discovered regions can assist to estimate target motion under severe occlusion, even if target tracker fails. Results: We evaluate the proposed method for pigtail tracking during TAVI. We obtain significant improvement (12 %) over the baseline in a clinical dataset. Calcification regions are automatically discovered during tracking, which would aid TAVI processes. Conclusion: In this work, we open a new paradigm to provide dynamic real-time guidance for TAVI without user interventions, specially in case of severe occlusion where conventional tracking methods are challenged.