The CNN-based Coronary Occlusion Site Localization with Effective Preprocessing Method
This work addresses a critical medical issue for patients with acute CAO, but it appears incremental as it focuses on enhancing preprocessing for a specific domain.
The paper tackled the problem of localizing Coronary Artery Occlusion (CAO) sites to aid in timely Percutaneous Coronary Intervention, improving localization performance from a minimum of 0.150 to a maximum of 0.372 using a noise reduction and pulse extraction preprocessing method.
The Coronary Artery Occlusion (CAO) acutely comes to human, and it highly threats the human's life. When CAO detected, Percutaneous Coronary Intervention (PCI) should be conducted timely. Before PCI, localizing the CAO is needed firstly, because the heart is covered with various arteries. We handle the three kinds of CAO in this paper and our purpose is not only localization of CAO but also improving the localizing performance via preprocessing method. We improve localization performance from a minimum of 0.150 to a maximum of 0.372 via our noise reduction and pulse extraction based method.