Cargando…
Preliminary study of multiple b-value diffusion-weighted images and T1 post enhancement magnetic resonance imaging images fusion with Laplacian Re-decomposition (LRD) medical fusion algorithm for glioma grading
BACKGROUND: Grade of brain tumor is thought to be the most significant and crucial component in treatment management. Recent development in medical imaging techniques have led to the introduce non-invasive methods for brain tumor grading such as different magnetic resonance imaging (MRI) protocols....
Autores principales: | Khorasani, Amir, Tavakoli, Mohamad Bagher, Saboori, Masih, Jalilian, Milad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487979/ https://www.ncbi.nlm.nih.gov/pubmed/34632000 http://dx.doi.org/10.1016/j.ejro.2021.100378 |
Ejemplares similares
-
Performance comparison of different medical image fusion algorithms for clinical glioma grade classification with advanced magnetic resonance imaging (MRI)
por: Khorasani, Amir, et al.
Publicado: (2023) -
A multi-focus image fusion method via region mosaicking on Laplacian pyramids
por: Kou, Liang, et al.
Publicado: (2018) -
An Image Fusion Method Based on Sparse Representation and Sum Modified-Laplacian in NSCT Domain
por: Li, Yuanyuan, et al.
Publicado: (2018) -
Single Image Defogging Method Based on Image Patch Decomposition and Multi-Exposure Image Fusion
por: Liu, Qiuzhuo, et al.
Publicado: (2021) -
Optimized data fusion for K-means Laplacian clustering
por: Yu, Shi, et al.
Publicado: (2011)