Post-Surgery Glioma Growth Modeling from Magnetic Resonance Images for Patients with Treatment
Abstract Reaction diffusion is the most common growth modelling methodology due to its simplicity and consistency with the biological tumor growth process. However, current extensions of the reaction diffusion model lack one or more of the following: efficient inclusion of treatments’ effects, takin...
Guardado en:
Autores principales: | Ahmed Elazab, Hongmin Bai, Yousry M. Abdulazeem, Talaat Abdelhamid, Sijie Zhou, Kelvin K. L. Wong, Qingmao Hu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
|
Materias: | |
Acceso en línea: | https://doaj.org/article/3a5d08776ed8437195f67b87192e0334 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Glioma-targeting micelles for optical/magnetic resonance dual-mode imaging
por: Zhou Q, et al.
Publicado: (2015) -
Failed Back Surgery Syndrome: Magnetic Resonance Imaging Assessment
por: Esam Hemat, et al.
Publicado: (2014) -
“Aerobic glycolytic imaging” of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging
por: Akifumi Hagiwara, et al.
Publicado: (2021) -
Magnetic resonance imaging
Publicado: (1982) -
Assessing the reproducibility of high temporal and spatial resolution dynamic contrast-enhanced magnetic resonance imaging in patients with gliomas
por: Woo Hyeon Lim, et al.
Publicado: (2021)