Implementation of a model for detection and classification of brain tumours in magnetic resonance imaging using convolutional neural networks
Accurate detection and classification of brain tumours in magnetic resonance imaging (MRI) are crucial for diagnosis and treatment planning. This research paper presents the implementation of a comprehensive model for the detection and classification of brain tumours using convolutional neural netwo...
Main Authors: | Serra-Parri, A. (Alvaro), Díaz-Dorronsoro, J. (Javier) |
---|---|
Format: | info:eu-repo/semantics/bachelorThesis |
Language: | eng |
Published: |
Servicio de Publicaciones. Universidad de Navarra.
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10171/67172 |
Similar Items
-
Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study
by: Guirado Hernández, Emilio, et al.
Published: (2020) -
Transvaginal ultrasound versus magnetic resonance imaging for diagnosing adenomyosis: A systematic review and head-to-head meta-analysis
by: Alcazar, J.L. (Juan Luis), et al.
Published: (2024) -
Tree Cover Estimation in Global Drylands from Space Using Deep Learning
by: Guirado Hernández, Emilio, et al.
Published: (2020) -
Electronics and Its Worldwide Research
by: García Salvador, Rosa María, et al.
Published: (2020) - Neuroendocrinology and brain peptides