# Pneumothorax and chest tube classification on chest x-rays for detection of missed pneumothorax

Source: [Pneumothorax and chest tube classification on chest x-rays for detection of missed pneumothorax](<https://www.sota2.com/research/paper/68fa68ba1e209131cea1dd5a>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T22:43:58.904Z

Authors: Benedikt Graf, Arkadiusz Sitek, Amin Katouzian, Yen-Fu Lu, Arun Krishnan, Justin Rafael, Kirstin Small, Yiting Xie

Published: 2020-11-14T18:06:06.000Z

## Abstract

Chest x-ray imaging is widely used for the diagnosis of pneumothorax and there has been significant interest in developing automated methods to assist in image interpretation. We present an image classification pipeline which detects pneumothorax as well as the various types of chest tubes that are commonly used to treat pneumothorax. Our multi-stage algorithm is based on lung segmentation followed by pneumothorax classification, including classification of patches that are most likely to contain pneumothorax. This algorithm achieves state of the art performance for pneumothorax classification on an open-source benchmark dataset. Unlike previous work, this algorithm shows comparable performance on data with and without chest tubes and thus has an improved clinical utility. To evaluate these algorithms in a realistic clinical scenario, we demonstrate the ability to identify real cases of missed pneumothorax in a large dataset of chest x-ray studies.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2011.07353>)

[PDF](<https://arxiv.org/pdf/2011.07353.pdf>)