Deep Learning for Automatic Pneumonia Detection

Abstract

Pneumonia is the leading cause of death among young children and one of the top mortality causes worldwide. The pneumonia detection is usually performed through examine of chest X-ray radiograph by highly-trained specialists. This process is tedious and often leads to a disagreement between radiologists. Computer-aided diagnosis systems showed the potential for improving diagnostic accuracy. In this work, we develop the computational approach for pneumonia regions detection based on single-shot detectors, squeeze-and-excitation deep convolution neural networks, augmentations and multi-task learning. The proposed approach was evaluated in the context of the Radiological Society of North America Pneumonia Detection Challenge, achieving one of the best results in the challenge.

arXiv commentto appear in CVPR 2020 Workshops proceedings

References in corpus (10)

• Very Deep Convolutional Networks for Large-Scale Image Recognition
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
• Deep Residual Learning for Image Recognition
• ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
• Confounding variables can degrade generalization performance of radiological deep learning models
• CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
• Benchmark Analysis of Representative Deep Neural Network Architectures
• Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
• Dual Path Networks

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• OXnet: Omni-supervised Thoracic Disease Detection from Chest X-rays
• Generative Residual Attention Network for Disease Detection