Examinando por Materia "Procesamiento de imágenes"
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Publicación Aplicación de métodos de visión artificial para la detección de huevos en una planta de producción avícola(Universidad EAFIT, 2024) Cardona Ortiz, César Augusto; Ortiz Arias, SantiagoPublicación Completion of input images of the elastic registration process for IMRT applied to breast cancer using spline-based interpolation(Universidad EAFIT, 2024) Ríos Querubín, Mateo; Rivera, Juan Carlos; Laniado, Henry; Puerta, María EugeniaCancer is one of the leading causes of death worldwide. Radiotherapy plays a fundamental role in its treatment, but the collateral damage of the process can affect patients' quality of life. Intensity-modulated radiation therapy (IMRT) is an advanced technique that offers promising benefits, but input imaging for IMRT incurs high costs. To mitigate collateral damage and increase treatment efficacy, we propose a methodology to expand the input set for IMRT. In this study, we focused on reducing the uncertainty of the data by preprocessing the input images. By employing bootstrapping, a non-parametric statistical sampling technique, we reduce the input images to regions of interest. Interpolating this information using polynomial splines and B-splines generates intermediate images. Our findings show that both interpolation methods, specifically the degree 1 polynomial spline, effectively reduce the uncertainty of the data. The methods are tested using Pearson correlation tests and bootstrap hypothesis tests, finding them accurate. By expanding the input data set and minimizing uncertainty, our approach promises to improve treatment planning and enhance patient outcomes in radiotherapy.Ítem Componentes para un sistema de análisis de imágenes de microscopio(Universidad EAFIT, 1997) Acosta Correa, Beatriz; Bermúdez A., Jaime; Universidad EAFITPublicación Detección temprana de melanoma : aplicación de técnicas de procesamiento de imágenes y aprendizaje profundo(Universidad EAFIT, 2025) Lacouture Fierro, Juan David; Álvarez Barrera, Claudia PatriciaSkin cancer is the most common type of cancer worldwide, with melanoma accounting for only 1% of cases but causing most deaths associated with this disease. In the United States, 97,610 new cases of melanoma were diagnosed in 2023, with a mortality rate of 7,990. In Colombia, the incidence of melanoma has increased significantly in recent years. According to the Cuenta de Alto Costo, 7,881 new cases were reported in 2024, with 11.94% of diagnoses concentrated in Bogotá and the Central region. Additionally, the total number of cases treated in the country increased from 53,622 in 2017 to more than 105,000 in 2021. These figures place Colombia as the fourth country in the Americas with the highest incidence of melanoma, highlighting the urgent need to implement innovative tools for early diagnosis. This project develops a deep learning model to diagnose melanoma through medical imaging, utilizing convolutional neural networks and advanced image processing techniques. The model includes data collection, training, and validation, aiming to deliver rapid and accurate diagnoses. The research encourages for the integration of artificial intelligence into medical practice, enabling early diagnosis in regions with limited access to specialists and alleviating the burden on the healthcare system. In conclusion, this initiative represents a milestone in dermatological care in Colombia, benefiting both high-incidence areas and rural communities.Ítem Visión y procesamiento de imágenes para control de calidad(Universidad EAFIT, 1996) Díaz Torres, Adalberto; Universidad EAFIT