2026-06-03T00:39:40Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/253912026-02-03T11:58:26Zcom_10630_2254col_10630_37959

Stenosis detection in coronary angiography images using deep learning models Luque-Baena, Rafael Marcos Romero Granados, Irene Jiménez-Partinen, Ariadna Palomo-Ferrer, Esteban José Procesado de imágenes Aprendizaje automático (Inteligencia artificial) Inteligencia artificial The emergence of deep learning has caused its massive application to different fields in industry and research, among which is the clinical field, especially in those where the data is structured in the form of images or video. The present proposal intends to develop a coronary angiography image analysis system based on artificial intelligence. These images are radiocontrast X-ray images of the coronary arteries. The proposed system will be able to analyze these coronary angiography images of patients with no obstructive coronary lesions to detect and characterize smooth and irregular coronary arteries and predict the presence of cardiovascular events during follow-up. Deep learning convolutional artificial neural networks will support the algorithmic basis of the proposed system. 2022-11-10T11:06:46Z 2022-11-10T11:06:46Z 2022 2022 conference output https://hdl.handle.net/10630/25391 eng 2022 IEEE INTERNATIONAL CONFERENCE ON METROLOGY FOR EXTENDED REALITY, ARTIFICIAL INTELLIGENCE AND NEURAL ENGINEERING Roma, Italia 26/10/2022 open access