Automated lumen segmentation using multi-frame convolutional neural networks in intravascular ultrasound datasets

AIMS: Assessment of minimum lumen areas in intravascular ultrasound (IVUS) pullbacks is time-consuming and demands adequately trained personnel. In this work, we introduce a novel and fully automated pipeline to segment the lumen boundary in IVUS datasets. METHODS AND RESULTS: First, an automated ga...

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Detalles Bibliográficos
Autores principales: Ziemer, Paulo G P, Bulant, Carlos A, Orlando, José I, Maso Talou, Gonzalo D, Álvarez, Luis A Mansilla, Guedes Bezerra, Cristiano, Lemos, Pedro A, García-García, Héctor M, Blanco, Pablo J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707866/
https://www.ncbi.nlm.nih.gov/pubmed/36713961
http://dx.doi.org/10.1093/ehjdh/ztaa014

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707866/
https://www.ncbi.nlm.nih.gov/pubmed/36713961
http://dx.doi.org/10.1093/ehjdh/ztaa014

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