YeongHyeon / Lung_Extraction_from_CXR

Lung Extraction from Chest X-ray for Efficient Computing

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Lung Extraction from CXR

This repository contains 'Lung Extaction System'. It need for efficient computing in registration between previous CXR and post CXR or etc. It is great for extracting 'Lung area' while minimizing loss of information in the original and cutting off unnecessary information. Its performance measured as following.
Precision: 0.788
Recall: 1.0
F1-score: 0.881

Flow Chart

Flowchart
Fig 1. The flowchart of the system.

CNN Structure

ResNet
Fig 2. The CNN model for classify each regions. It constructed ResNet like model.

Sample of Dataset

Datasample
Fig 3. Sample data of training dataset. These are reflects shape and texture of data that pre-processed by contouring and masking.

Dataset: Chest X-ray8 from NIH. (Total 112120 CXR images.)

Result

Result
Fig 4. Result of the system. The blue box is ROI of CXR that interested on lung. The red vox is ROI of diagnosis that annotated by NIH.

About

Lung Extraction from Chest X-ray for Efficient Computing

License:MIT License


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Language:Python 100.0%