  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.
