Detección automática de anomalías cerebro vascular a través de resonancia magnética aplicando métodos de análisis avanzados con inteligencia artificial en pacientes no diagnosticados.
| dc.contributor.advisor | Soto Valle, Carlos Julio | |
| dc.contributor.author | Robles Bravo, Leonardo Ismael | |
| dc.date.accessioned | 2024-08-21T19:12:00Z | |
| dc.date.available | 2024-08-21T19:12:00Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | http://dspace.utb.edu.ec/handle/49000/16986 | |
| dc.description | This research addresses the development of a brain tumor detection system using AI techniques applied to magnetic resonance (MR) images in the diagnoses of the health center of the rural Pimocha parish of the canton of Babahoyo, province of Los Rios in the year 2024. The automated detection of cerebrovascular anomalies using magnetic resonance imaging and analysis techniques based on artificial intelligence actually represents a major advance in diagnostic medicine. The approach leverages the ability of MRI to create detailed images of the brain with the ability of artificial intelligence to identify subtle and complex patterns that could indicate cerebrovascular conditions, including aneurysms, arteriovenous malformations, ischemic strokes and hemorrhages. Brain tumors are a problematic aspect of medical diagnosis not only because they are a complicated form, but also because of their presence in brain tissue; Furthermore, tumor identification based on manual methods depends on expert radiologists and is subjective. Deep modeling was a technique for localization and classification of brain tumors that embraces the advancements of AI to develop an assistive tool for the doctor. | es_ES |
| dc.description | This research addresses the development of a brain tumor detection system using AI techniques applied to magnetic resonance (MR) images in the diagnoses of the health center of the rural Pimocha parish of the canton of Babahoyo, province of Los Rios in the year 2024. The automated detection of cerebrovascular anomalies using magnetic resonance imaging and analysis techniques based on artificial intelligence actually represents a major advance in diagnostic medicine. The approach leverages the ability of MRI to create detailed images of the brain with the ability of artificial intelligence to identify subtle and complex patterns that could indicate cerebrovascular conditions, including aneurysms, arteriovenous malformations, ischemic strokes and hemorrhages. Brain tumors are a problematic aspect of medical diagnosis not only because they are a complicated form, but also because of their presence in brain tissue; Furthermore, tumor identification based on manual methods depends on expert radiologists and is subjective. Deep modeling was a technique for localization and classification of brain tumors that embraces the advancements of AI to develop an assistive tool for the doctor. | es_ES |
| dc.description.abstract | En esta investigación se aborda el desarrollo de un sistema de detección de tumores cerebrales utilizando técnicas de IA aplicadas a imágenes de resonancia magnética (RM) en los diagnósticos del centro de salud de la parroquia rural pimocha del cantón de Babahoyo provincia de los Ríos en el año 2024. La detección automatizada de anomalías cerebrovasculares utilizando la resonancia magnética y técnicas de análisis basadas en inteligencia artificial, en realidad, representa un gran avance en medicina diagnóstica. El enfoque aprovecha la capacidad de la resonancia magnética para crear imágenes detalladas del cerebro con la capacidad de la inteligencia artificial para identificar patrones sutiles y complejos que podrían indicar afecciones cerebrovasculares, incluyendo aneurismas, malformaciones arteriovenosas, accidentes cerebrovasculares isquémicos y hemorragias. Los tumores cerebrales son un aspecto problemático del diagnóstico médico no solo por ser una forma complicada, sino también por su presencia en el tejido cerebral; además, la identificación de tumores basada en métodos manuales depende de radiólogos expertos y es subjetiva. El modelo profundo fue una técnica para la localización y clasificación de los tumores cerebrales que adopta los avances de la IA para desarrollar una herramienta de asistencia para el médico. | es_ES |
| dc.format.extent | 52 p. | es_ES |
| dc.language.iso | es | es_ES |
| dc.publisher | Babahoyo: UTB-FAFI. 2024 | es_ES |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Ecuador | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ec/ | * |
| dc.subject | Resonancia Magnética | es_ES |
| dc.subject | Inteligencia Artificial | es_ES |
| dc.subject | Aprendizaje Profundo | es_ES |
| dc.subject | Detección Automática | es_ES |
| dc.title | Detección automática de anomalías cerebro vascular a través de resonancia magnética aplicando métodos de análisis avanzados con inteligencia artificial en pacientes no diagnosticados. | es_ES |
| dc.type | bachelorThesis | es_ES |
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Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 Ecuador