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Revolutionizing Cardiac Ablation: Machine Learning-Driven Segmentation of Computed Tomograms

Andrea Kennet

Cardiac ablation, a procedure in treating cardiac arrhythmias, demands precision and accuracy in targeting abnormal heart tissue. Computed Tomography (CT) scans play a pivotal role in planning such interventions. However, the manual segmentation of these scans to identify relevant anatomical structures can be time-consuming and prone to errors. Leveraging the power of machine learning, particularly with domain knowledge encoding, presents the way for automating and enhancing this segmentation process