EventsMOL2NET'18, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 4th ed.
Published
This submission belongs to the session 04. AIMEDIC-06: AI, Med. Info., & Biomed. Eng. Congress, Coruña, Spain-Miami, USA, 2018. of the event MOL2NET'18, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 4th ed.
Published date
05 Sep, 2018
Citation
Adrian Carballal, Carlos Fernandez-Lozano, Francisco J. Novoa, Nereida Rodriguez-Fernandez, Iria Santos, Marcos Garcia-Guimaraes, Guillermo Aldama-Lopez, Ramon Calviño-Santos, Jose Manuel Vazquez-Rodriguez, Alejandro Pazos, Redesign and performance of an automatic segmentation method, in Proceedings of MOL2NET'18, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 4th ed., 15 January 2018–20 January 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-04-05501
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Redesign and performance of an automatic segmentation method

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Marcos Garcia-Guimaraes 2
Guillermo Aldama-Lopez 2
Ramon Calviño-Santos 2
Jose Manuel Vazquez-Rodriguez 2
Alejandro Pazos 1
1. Computer Science Department, University of A Coruña
2. Department of Cardiology, Complexo Hospitalario Universitario de A Coruña
Abstract

La información más relevante de las angiografías coronarias se extrae empleando técnicas de segmentación, que pueden ser automáticas, semiautomáticas o manuales. Existen numerosos algoritmos de segmentación vascular, obteniendo mejores resultados, por normal general, aquellos que emplean múltiples técnicas e imágenes a diferentes escalas para proporcionar los resultados requeridos. Se presenta un nuevo método de segmentación automatizado basado en el método manual de Hamarneh incluyendo un estudio estadístico que demuestra su idoneidad para el problema.

Keywords
Coronary segmentation
angiography
Manuscript
Poster
Redesing Segmentation_poster.pdf
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