AI-driven View Guidance System in Intra-cardiac Echocardiography Imaging

Abstract-- Intra-cardiac Echocardiography (ICE) is a crucial imaging modality used in electrophysiology (EP) and structural heart disease (SHD) interventions, providing realtime, high-resolution views from within the heart. Despite its advantages, effective manipulation of the ICE catheter requires significant expertise, which can lead to inconsistent outcomes, particularly among less experienced operators. To address this challenge, we propose an AIdriven closed-loop view guidance system with human-inthe-loop feedback, designed to assist users in navigating ICE imaging without requiring specialized knowledge. Our method models the relative position and orientation vectors between arbitrary views and clinically defined ICE views in a spatial coordinate system, guiding users on how to manipulate the ICE catheter to transition from the current view to the desired view over time. Overview of the proposed view guidance system. The primary use cases of the ICE imaging involve visualizing target anatomy, detecting and tracking therapeutic devices, and validating treatments in real-time. HE Intra-cardiac Echocardiography (ICE) is a sophisticated imaging modality that offers real-time, highresolution have significant expertise in interpreting anatomical views views from within the heart, making it an invaluable via ICE images and skillfully maneuvering the ICE catheter tool in both electrophysiology (EP) and structural heart disease using two knobs (anterior-posterior, right-left) and the rotating/translating (SHD) interventions.