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Corrigendum: Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg.
Suh, Pae Sun; Jung, Wooseok; Suh, Chong Hyun; Kim, Jinyoung; Oh, Jio; Heo, Hwon; Shim, Woo Hyun; Lim, Jae-Sung; Lee, Jae-Hong; Kim, Ho Sung; Kim, Sang Joon.
Afiliación
  • Suh PS; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Jung W; R&D Center, VUNO, Seoul, Republic of Korea.
  • Suh CH; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Kim J; R&D Center, VUNO, Seoul, Republic of Korea.
  • Oh J; R&D Center, VUNO, Seoul, Republic of Korea.
  • Heo H; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Shim WH; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Lim JS; Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Lee JH; Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Kim HS; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Kim SJ; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Front Neurol ; 14: 1334962, 2023.
Article en En | MEDLINE | ID: mdl-38093753
ABSTRACT
[This corrects the article DOI 10.3389/fneur.2023.1221892.].
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Neurol Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Neurol Año: 2023 Tipo del documento: Article
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