Brain Tumor Segmentation Network with Multi-View Ensemble Discrimination and Kernel-Sharing Dilated Convolution

Accurate segmentation of brain tumors from magnetic resonance 3D images (MRI) is critical for clinical decisions and surgical planning. Radiologists usually separate and analyze brain tumors by combining images of axial, coronal, and sagittal views. However, traditional convolutional neural network...

Descripción completa

Detalles Bibliográficos
Autores principales: Guan, Xin, Zhao, Yushan, Nyatega, Charles Okanda, Li, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10136543/
https://www.ncbi.nlm.nih.gov/pubmed/37190614
http://dx.doi.org/10.3390/brainsci13040650

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10136543/
https://www.ncbi.nlm.nih.gov/pubmed/37190614
http://dx.doi.org/10.3390/brainsci13040650

Ejemplares similares