Skip to content

About

Using an External dataset to get the pre-trained weights of the NIH dataset and training on the provided dataset to detect the presence of pneumonia.

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Latest commit

 

History

3 Commits

Folders and files

Repository files navigation

PneumoniaDetection

Pneumonia Classification in Chest X-Rays (CXRs) is organized by Segmind. As you maybe aware, "Pneumonia killed more than 808,000 children under the age of 5 in 2017, accounting for 15% of all deaths of children under 5 years. People at-risk for pneumonia also include adults over the age of 65 and people with preexisting health problems." — WHO

While prevalent, diagnosing pneumonia in a CXR accurately is difficult. Expert radiologists are required to review the CXR and also require confirmation through clinical examinations. To classify CXRs with pneumonia from their normal CXR counterparts, using machine learning and computer vision techniques.

About the Dataset

It consists of 2425 CXRs for training and 606 CXRs for testing. Training data: 1145 Pneumonia CXRs and 1280 Normal CXRs. Every CXR is a 1024 X 1024 image in the PNG format.

The labels for each CXR were extracted using an NLP label extractor from corresponding radiology reports.

About

Using an External dataset to get the pre-trained weights of the NIH dataset and training on the provided dataset to detect the presence of pneumonia.

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages