A Deep Learning Model with High Standalone Performance for Diagnosis of Unruptured Intracranial Aneurysm

PURPOSE: This study aimed to investigate whether a deep learning model for automated detection of unruptured intracranial aneurysms on time-of-flight (TOF) magnetic resonance angiography (MRA) can achieve a target diagnostic performance comparable to that of human radiologists for approval from the...

Descripción completa

Detalles Bibliográficos
Autores principales: Joo, Bio, Choi, Hyun Seok, Ahn, Sung Soo, Cha, Jihoon, Won, So Yeon, Sohn, Beomseok, Kim, Hwiyoung, Han, Kyunghwa, Kim, Hwa Pyung, Choi, Jong Mun, Lee, Sang Min, Kim, Tae Gyu, Lee, Seung-Koo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Yonsei University College of Medicine 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542476/
https://www.ncbi.nlm.nih.gov/pubmed/34672139
http://dx.doi.org/10.3349/ymj.2021.62.11.1052

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542476/
https://www.ncbi.nlm.nih.gov/pubmed/34672139
http://dx.doi.org/10.3349/ymj.2021.62.11.1052

Ejemplares similares