Publication: Reconocimiento de imágenes médicas mediante aprendizaje automático
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2021
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Abstract
Este proyecto trata de aplicar técnicas de deep learning para solucionar un problema de categorización con múltiples etiquetas en imágenes médicas. En concreto, se utiliza un corpus de radiografías de pulmón con cuatro etiquetas: Normal, COVID-19, Opacidad de Pulmón y Neumonía Viral.El trabajo consta de un estudio inicial de las técnicas de reconocimiento de imagen usando deep learning, tratando los tipos de redes neuronales más comunes y los conceptos claves en el entrenamiento de estas. También se tratan conceptos más avanzados de las redes convolucionales que permitirán mejorar algunos puntos el rendimiento del modelo. Además, se realiza una experimentación sencilla con redes neuronales que identifican letras a modo de introducción a la tecnología. Finalmente, se proponen una serie de modelos para solventar el problema, se entrenan y se evalúan los resultados. Se ha llegado a conseguir una exactitud de 92,91% en el conjunto de validación, lo cual es un resultado bastante satisfactorio, teniendo en cuenta el problema planteado.
The purpose of this project is to apply deep learning techniques to solve a multi label classification problem with medical images. For that, a corpus of lung radiographies with four labels (Normal, COVID-19, Lung Opacity and Viral Pneumonia) will be used. The initial part of the project will consist in an study of the image recognition deep learning techniques. Most common types of neural networks will be explained as well as the fundamental concepts of their training. More advanced topics will also be treated such as separable convolutional layers or augmentation and batch normalization techniques. After that, a letter recognition problem will be solved using convolutional neural networks to get familiarized with the technology. Finally, several models will be proposed and trained for the medical image problems, following with an evaluation of the results. An accuracy of 92.91% was acquired in the validation set, which is definitely a good result taking into account the proposed problem.
The purpose of this project is to apply deep learning techniques to solve a multi label classification problem with medical images. For that, a corpus of lung radiographies with four labels (Normal, COVID-19, Lung Opacity and Viral Pneumonia) will be used. The initial part of the project will consist in an study of the image recognition deep learning techniques. Most common types of neural networks will be explained as well as the fundamental concepts of their training. More advanced topics will also be treated such as separable convolutional layers or augmentation and batch normalization techniques. After that, a letter recognition problem will be solved using convolutional neural networks to get familiarized with the technology. Finally, several models will be proposed and trained for the medical image problems, following with an evaluation of the results. An accuracy of 92.91% was acquired in the validation set, which is definitely a good result taking into account the proposed problem.
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