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Abbott Electrophysiology: Detection of cardiac ablation lesions in Intracardiac Echocardiography

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Create an image segmentation algorithm capable of detecting lesions from cardiac ablation in real time.

Project Overview

Catheter ablation is a cornerstone therapy for cardiac arrhythmias, and its success relies heavily on the accurate creation and assessment of ablation lesions. Current evaluation methods in electrophysiology (EP) labs, particularly when using intracardiac echocardiography (ICE), are limited by human error and the inherent difficulty of visualizing lesion boundaries and depth in real time. These challenges are compounded by the use of two distinct energy modalities: radiofrequency (RF), which produces thermally induced scars of variable depth, and pulsed field ablation (PFA), which generates non-thermal lesions via electroporation. The lack of standardized, automated methods to reliably detect and characterize these lesions in ICE images leads to variability in procedural outcomes, reduced accuracy in lesion delivery, and potential long-term inefficacy of treatment. Therefore, there is a critical need for a software-based solution that can automatically detect and highlight ablation lesions on ICE images, accommodating both RF and PFA-induced tissue changes, to support real-time decision-making, reduce operator dependence, and improve the consistency and effectiveness of catheter ablation procedures.

Team Picture

Team Photo: (Left to Right) Zach Harmon, Anya Hadim, Jose Ramirez, Edward Han, Shuyan Zhang
Team Photo: (Left to Right) Zach Harmon, Anya Hadim, Jose Ramirez, Edward Han, Shuyan Zhang

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Team Members

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