# Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax

Source: [Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax](<https://www.sota2.com/research/paper/68fa74c21e209131cea63925>)

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

Data updated: 2025-10-26T03:17:28.990Z

Authors: Karan Jakhar, Avneet Kaur, Meenu Gupta

Published: 2019-12-16T13:00:32.000Z

## Abstract

Computer vision has shown promising results in medical image processing. Pneumothorax is a deadly condition and if not diagnosed and treated at time then it causes death. It can be diagnosed with chest X-ray images. We need an expert and experienced radiologist to predict whether a person is suffering from pneumothorax or not by looking at the chest X-ray images. Everyone does not have access to such a facility. Moreover, in some cases, we need quick diagnoses. So we propose an image segmentation model to predict and give the output a mask that will assist the doctor in taking this crucial decision. Deep Learning has proved their worth in many areas and outperformed man state-of-the-art models. We want to use the power of these deep learning model to solve this problem. We have used U-net \[13\] architecture with ResNet \[17\] as a backbone and achieved promising results. U-net \[13\] performs very well in medical image processing and semantic segmentation. Our problem falls in the semantic segmentation category.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1912.07329>)

[PDF](<https://arxiv.org/pdf/1912.07329.pdf>)