Classification of pulmonary diseases using convolutional neural networks

# Deep Learning applied to Radiology

Este repositório contém uma investigação sobre o uso de algoritmos de Aprendizado Profundo em tarefas de diagnóstico radiológico. Em particular, o foco é a classificação de distúrbios pulmonares em radiografias de tórax, usando técnicas Redes Neurais Convolucionais e Processamento de Imagens Digitais.

### Context

Radiology is a medical specialty that relies on extracting information from images to diagnose diseases and guide the treatment of patients. This task can be challenging as it requires a great deal of specialized knowledge and practical experience. Fortunately, Deep Learning offers a powerful way to automate image analysis and provide doctors with valuable information to help with diagnosis.

### Goal

This repository aims to explore the use of Convolutional Neural Network models to classify lung disorders on chest X-rays. In particular, the disorders studied are Opacity, Atelectasis, Pneumothorax and Pleural Effusion. For this, Digital Image Processing techniques, reuse of Convolutional Neural Network architectures and Classification Committees are used.

### Results

The models constructed present an Accuracy of 87.77%, Accuracy of 91.96%, Sensitivity of 90.24% and F1-Score of 91.07% in the multilabel classification of chest X-rays. In addition, an interpretability analysis of the models is performed, using Activation Map algorithms to extract useful visual information and compare the results with examinations reported by radiologists.


Keras Libraries - Page 321

cnn-lung-diseasesby Alyssonmach

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Classification of pulmonary diseases using convolutional neural networks

cnn-lung-diseasesby Alyssonmach

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Keras Libraries - Page 321

cnn-lung-diseasesby Alyssonmach

Jupyter Notebook 0 Version:Current License: Permissive (MIT)

Classification of pulmonary diseases using convolutional neural networks

cnn-lung-diseasesby Alyssonmach

Open Weaver – Develop Applications Faster with Open Source

kandi

Community and Support

Company

Follow

Jupyter Notebook 0 Version:Current
License: Permissive (MIT)