Assessment of New Coronary Features on Quantitative Coronary Angiographic Images With Innovative Unsupervised Artificial Adaptive Systems: A Proof-of-Concept Study

Background and Purpose: The Active Connection Matrixes (ACMs) are unsupervised artificial adaptive systems able to extract from digital images features of interest (edges, tissue differentiation, etc.) unnoticeable with conventional systems. In this proof-of-concept study, we assessed the potentiali...

Descripción completa

Detalles Bibliográficos
Autores principales: Amato, Mauro, Buscema, Massimo, Massini, Giulia, Maurelli, Guido, Grossi, Enzo, Frigerio, Beatrice, Ravani, Alessio L., Sansaro, Daniela, Coggi, Daniela, Ferrari, Cristina, Bartorelli, Antonio L., Veglia, Fabrizio, Tremoli, Elena, Baldassarre, Damiano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551448/
https://www.ncbi.nlm.nih.gov/pubmed/34722664
http://dx.doi.org/10.3389/fcvm.2021.730626

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551448/
https://www.ncbi.nlm.nih.gov/pubmed/34722664
http://dx.doi.org/10.3389/fcvm.2021.730626

Ejemplares similares