Deep Learning for Pneumothorax Detection and Localization in Chest Radiographs

07/16/2019
by   André Gooßen, et al.
0

Pneumothorax is a critical condition that requires timely communication and immediate action. In order to prevent significant morbidity or patient death, early detection is crucial. For the task of pneumothorax detection, we study the characteristics of three different deep learning techniques: (i) convolutional neural networks, (ii) multiple-instance learning, and (iii) fully convolutional networks. We perform a five-fold cross-validation on a dataset consisting of 1003 chest X-ray images. ROC analysis yields AUCs of 0.96, 0.93, and 0.92 for the three methods, respectively. We review the classification and localization performance of these approaches as well as an ensemble of the three aforementioned techniques.

READ FULL TEXT
research
04/21/2022

Chest Radiographs Classification Using Multi-model Deep Learning: A Comparative Study

Respiratory diseases have been a main reason for death in many countries...
research
03/24/2020

Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks

The 2019 novel coronavirus (COVID-19), with a starting point in China, h...
research
06/07/2020

A Comparative Study on Early Detection of COVID-19 from Chest X-Ray Images

In this study, our first aim is to evaluate the ability of recent state-...
research
11/21/2018

Pneumonia Detection in Chest Radiographs

In this work, we describe our approach to pneumonia classification and l...
research
10/13/2022

OOOE: Only-One-Object-Exists Assumption to Find Very Small Objects in Chest Radiographs

The accurate localization of inserted medical tubes and parts of human a...
research
06/02/2020

Real-time Earthquake Early Warning with Deep Learning: Application to the 2016 Central Apennines, Italy Earthquake Sequence

Earthquake early warning systems are required to report earthquake locat...
research
08/28/2023

Comparing AutoML and Deep Learning Methods for Condition Monitoring using Realistic Validation Scenarios

This study extensively compares conventional machine learning methods an...

Please sign up or login with your details

Forgot password? Click here to reset