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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: 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: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-10-01
Schriftenreihe:Technologies
Schlagworte:
convolutional neural networks
semantic segmentation
magnetic resonance image
UNET
Online-Zugang:https://www.mdpi.com/2227-7080/12/10/183
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