Cargando…
Rotation-invariant multi-contrast non-local means for MS lesion segmentation
Multiple sclerosis (MS) lesion segmentation is crucial for evaluating disease burden, determining disease progression and measuring the impact of new clinical treatments. MS lesions can vary in size, location and intensity, making automatic segmentation challenging. In this paper, we propose a new s...
Autores principales: | Guizard, Nicolas, Coupé, Pierrick, Fonov, Vladimir S., Manjón, Jose V., Arnold, Douglas L., Collins, D. Louis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474283/ https://www.ncbi.nlm.nih.gov/pubmed/26106563 http://dx.doi.org/10.1016/j.nicl.2015.05.001 |
Ejemplares similares
-
Non-Local Means Inpainting of MS Lesions in Longitudinal Image Processing
por: Guizard, Nicolas, et al.
Publicado: (2015) -
Longitudinal detection of new MS lesions using deep learning
por: Kamraoui, Reda Abdellah, et al.
Publicado: (2022) -
Scoring by nonlocal image patch estimator for early detection of Alzheimer's disease()
por: Coupé, Pierrick, et al.
Publicado: (2012) -
Jacobian integration method increases the statistical power to measure gray matter atrophy in multiple sclerosis()
por: Nakamura, Kunio, et al.
Publicado: (2013) -
A novel deep learning based hippocampus subfield segmentation method
por: Manjón, José V., et al.
Publicado: (2022)