The CNN-based Coronary Occlusion Site Localization with Effective Preprocessing Method

Autor:	Park, YeongHyeon, Yun, Il Dong, Kang, Si-Hyuck
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Druh dokumentu:	Working Paper
DOI:	10.1002/tee.23225
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1912.08375 Zobrazit plný text záznamu View this record from Arxiv