Cargando…
A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images
Computerized brain tumor classification from the reconstructed microwave brain (RMB) images is important for the examination and observation of the development of brain disease. In this paper, an eight-layered lightweight classifier model called microwave brain image network (MBINet) using a self-or...
Autores principales: | Hossain, Amran, Islam, Mohammad Tariqul, Abdul Rahim, Sharul Kamal, Rahman, Md Atiqur, Rahman, Tawsifur, Arshad, Haslina, Khandakar, Amit, Ayari, Mohamed Arslane, Chowdhury, Muhammad E. H. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954219/ https://www.ncbi.nlm.nih.gov/pubmed/36832004 http://dx.doi.org/10.3390/bios13020238 |
Ejemplares similares
-
Brain Tumor Segmentation and Classification from Sensor-Based Portable Microwave Brain Imaging System Using Lightweight Deep Learning Models
por: Hossain, Amran, et al.
Publicado: (2023) -
Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array
por: Hossain, Amran, et al.
Publicado: (2022) -
A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system
por: Hossain, Amran, et al.
Publicado: (2022) -
Metasurface-Enhanced Antennas for Microwave Brain Imaging
por: Razzicchia, Eleonora, et al.
Publicado: (2021) -
Microwave Imaging Sensor Using Compact Metamaterial UWB Antenna with a High Correlation Factor
por: Islam, Md. Moinul, et al.
Publicado: (2015)