Brain Tumor Segmentation from Optimal MRI Slices Using a Lightweight U-Net

Brain Tumor Segmentation from Optimal MRI Slices Using a Lightweight U-Net

The timely detection and accurate localization of brain tumors is crucial in preserving people’s quality of life. Thankfully, intelligent computational systems have proven invaluable in addressing these challenges. In particular, the UNET model can extract essential pixel-level features to automatic...

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Bibliographic Details
Main Authors: Fernando Daniel Hernandez-Gutierrez, Eli Gabriel Avina-Bravo, Daniel F. Zambrano-Gutierrez, Oscar Almanza-Conejo, Mario Alberto Ibarra-Manzano, Jose Ruiz-Pinales, Emmanuel Ovalle-Magallanes, Juan Gabriel Avina-Cervantes
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Technologies
Subjects:
convolutional neural networks
semantic segmentation
magnetic resonance image
UNET
Online Access:https://www.mdpi.com/2227-7080/12/10/183

Internet

https://www.mdpi.com/2227-7080/12/10/183

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