Our project is dedicated to advancing the treatment of atrial tachycardia (AT), a condition characterized by rapid heartbeats and often accompanied by symptoms like palpitations and shortness of breath. Despite advancements, accurately identifying the specific areas of heart tissue contributing to AT remains challenging, especially in complex cases. Previous pioneering research in our group has demonstrated that utilizing the index theorem, a mathematical principle, reveals the absence of single electrical circuits, necessitating the search for a second circuit. These circuits revolve around critical boundaries (CBs) that require connection with ablation therapy to halt the AT. CBs can encompass natural openings like the mitral valve or a vein, as well as areas beyond these, such as scar tissue, fibrotic tissue, or zones of conduction block. However, we still require manual intervention to cut-out regions of interest. Therefore, the goal of this project is to automatically identify CBs and seamlessly integrate this capability into our existing software package, Directed Graph Mapping (DGM), which harnesses network theory to identify if a region is a CB. We propose several techniques beyond the current state of the art, leveraging the powerful index theorem to precisely identify locations of possible CBs, beyond natural openings. This advancement holds promise for delivering precise, complete and simple ablation strategies for any given reentry AT cases.