Utilización de redes neuronales y resonancias magnéticas T2 y T2-FLAIR para la detección de lesiones periventriculares de esclerosis múltiple
| dc.contributor.advisor | Duitama Leal, Alejandro | |
| dc.contributor.advisor | Reyes, Marco Aurelio | |
| dc.contributor.author | Villamil Martinez, Cristian Andres | |
| dc.date.accessioned | 2025-07-10T21:40:26Z | |
| dc.date.available | 2025-07-10T21:40:26Z | |
| dc.date.issued | 2023-11 | |
| dc.description.abstract | Este estudio tuvo como objetivo desarrollar un modelo de red neuronal convolucional para la detección de esclerosis múltiple utilizando imágenes de MRI T2 y T2-FLAIR. Se creó una base de datos a partir de 36 estudios diferentes y la base de datos de Kaggle, incluyendo tanto MRI sin esclerosis múltiple como MRI con esclerosis múltiple. El modelo desarrollado alcanzó una precisión de verificación del 96%. Estos hallazgos destacan el potencial de las redes neuronales convolucionales en la detección de enfermedades a través de imágenes médicas, a pesar de algunas limitaciones, como el tamaño del conjunto de datos y las restricciones en la optimización de hiperparámetros. | |
| dc.description.abstractenglish | This study aimed at developing a convolutional neural network model for the detection of multiple sclerosis using T2 and T2-FLAIR MRI images. A database was created from 36 different studies and the Kaggle database, including both MRI without MS and MRI with MS. The developed model achieved a verification accuracy of 96%. These findings highlight the potential of convolutional neural networks in disease detection through medical imaging, despite some limitations such as dataset size and hyperparameter optimization constraints. | |
| dc.description.degreelevel | Pregrado | spa |
| dc.description.degreename | Matemático | spa |
| dc.format.mimetype | application/pdf | |
| dc.identifier.instname | instname:Universidad El Bosque | spa |
| dc.identifier.reponame | reponame:Repositorio Institucional Universidad El Bosque | spa |
| dc.identifier.repourl | repourl:https://repositorio.unbosque.edu.co | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12495/14922 | |
| dc.language.iso | es | |
| dc.publisher.faculty | Facultad de Ciencias | spa |
| dc.publisher.grantor | Universidad El Bosque | spa |
| dc.publisher.program | Matemáticas | spa |
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| dc.rights | Attribution-NoDerivatives 4.0 International | en |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.accessrights | https://purl.org/coar/access_right/c_abf2 | |
| dc.rights.local | Acceso abierto | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/4.0/ | |
| dc.subject | Red neuronal convolucional | |
| dc.subject | Esclerosis múltiple | |
| dc.subject | Resonancia magnética T2 y T2-FLAIR | |
| dc.subject | Base de datos Kaggle | |
| dc.subject | Optimización de hiperparámetros | |
| dc.subject.ddc | 510 | |
| dc.subject.keywords | Convolutional Neural Network | |
| dc.subject.keywords | Multiple Sclerosis | |
| dc.subject.keywords | T2 and T2- FLAIR MRI | |
| dc.subject.keywords | Kaggle Database | |
| dc.subject.keywords | Hyperparameter Optimization | |
| dc.title | Utilización de redes neuronales y resonancias magnéticas T2 y T2-FLAIR para la detección de lesiones periventriculares de esclerosis múltiple | |
| dc.title.translated | Use of neural networks and T2 and T2-FLAIR magnetic resonances for the detection of periventricular lesions in multiple sclerosis | |
| dc.type.coar | https://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | https://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | |
| dc.type.local | Tesis/Trabajo de grado - Monografía - Pregrado | spa |
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