Cargando…
Deep Convolutional Neural Network With a Multi-Scale Attention Feature Fusion Module for Segmentation of Multimodal Brain Tumor
As a non-invasive, low-cost medical imaging technology, magnetic resonance imaging (MRI) has become an important tool for brain tumor diagnosis. Many scholars have carried out some related researches on MRI brain tumor segmentation based on deep convolutional neural networks, and have achieved good...
Autores principales: | He, Xueqin, Xu, Wenjie, Yang, Jane, Mao, Jianyao, Chen, Sifang, Wang, Zhanxiang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662724/ https://www.ncbi.nlm.nih.gov/pubmed/34899175 http://dx.doi.org/10.3389/fnins.2021.782968 |
Ejemplares similares
-
An optimized deep convolutional neural network for adaptive learning using feature fusion in multimodal data
por: Gupta, Swadha, et al.
Publicado: (2023) -
Instance segmentation convolutional neural network based on multi-scale attention mechanism
por: Gaihua, Wang, et al.
Publicado: (2022) -
PCF-Net: Position and context information fusion attention convolutional neural network for skin lesion segmentation
por: Jiang, Yun, et al.
Publicado: (2023) -
Convolutional Neural Network Approach Based on Multimodal Biometric System with Fusion of Face and Finger Vein Features
por: Wang, Yang, et al.
Publicado: (2022) -
Adaptive Attention Convolutional Neural Network for Liver Tumor Segmentation
por: Luan, Shunyao, et al.
Publicado: (2021)