Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study
Guardado en:
Autores principales: | Akshay S. Chaudhari, Erik Mittra, Guido A. Davidzon, Praveen Gulaka, Harsh Gandhi, Adam Brown, Tao Zhang, Shyam Srinivas, Enhao Gong, Greg Zaharchuk, Hossein Jadvar |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/694b64e18fc1473c8c71444dcdab9b6e |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Low-count whole-body PET with deep learning in a multicenter and externally validated study
por: Akshay S. Chaudhari, et al.
Publicado: (2021) -
Multi-task weak supervision enables anatomically-resolved abnormality detection in whole-body FDG-PET/CT
por: Sabri Eyuboglu, et al.
Publicado: (2021) -
Usefulness of semi-automatic harmonization strategy of standardized uptake values for multicenter PET studies
por: Hiromitsu Daisaki, et al.
Publicado: (2021) -
68Ga-PSMA11 PET/CT for biochemically recurrent prostate cancer: Influence of dual-time and PMT- vs SiPM-based detectors
por: Heying Duan, et al.
Publicado: (2022) -
Automated coronary calcium scoring using deep learning with multicenter external validation
por: David Eng, et al.
Publicado: (2021)