Cargando…
Quantitative evaluation of the influence of multiple MRI sequences and of pathological tissues on the registration of longitudinal data acquired during brain tumor treatment
Registration methods facilitate the comparison of multiparametric magnetic resonance images acquired at different stages of brain tumor treatments. Image-based registration solutions are influenced by the sequences chosen to compute the distance measure, and the lack of image correspondences due to...
Autores principales: | Canalini, Luca, Klein, Jan, Waldmannstetter, Diana, Kofler, Florian, Cerri, Stefano, Hering, Alessa, Heldmann, Stefan, Schlaeger, Sarah, Menze, Bjoern H., Wiestler, Benedikt, Kirschke, Jan, Hahn, Horst K. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406206/ https://www.ncbi.nlm.nih.gov/pubmed/37555157 http://dx.doi.org/10.3389/fnimg.2022.977491 |
Ejemplares similares
-
BraTS Toolkit: Translating BraTS Brain Tumor Segmentation Algorithms Into Clinical and Scientific Practice
por: Kofler, Florian, et al.
Publicado: (2020) -
Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment
por: Waldmannstetter, Diana, et al.
Publicado: (2020) -
Hemodynamic MRI parameters to predict asymptomatic unilateral carotid artery stenosis with random forest machine learning
por: Gleißner, Carina, et al.
Publicado: (2023) -
Deep learning-based segmentation of brain parenchyma and ventricular system in CT scans in the presence of anomalies
por: Gerken, Annika, et al.
Publicado: (2023) -
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
por: Graf, Robert, et al.
Publicado: (2023)