Lung Image Analysis Framwork

A basic framework for pulmonary nodule detection and characterization in CT
https://github.com/taznux/lung-image-analysis

Tested on LIDC-IDRI dataset (https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI)

  • LIDC XML parsing
  • Simple lung segmentation, nodule detection, and feature extraction algorithms
  • Evaluation of nodule segmentation, detection, and characterization by LIDC XML annotations

written in Matlab by Wookjin Choi and Ji-Seok Yoon

 

This framework is the essential parts of the following papers.

  1. Wookjin Choi, Tae-Sun Choi, “Automated Pulmonary Nodule Detection based on Three-dimensional Shape-based Feature Descriptor”, Computer Methods and Programs in Biomedicine, Vol. 113, No. 1, January 2014, pp. 37–54, doi: http://dx.doi.org/10.1016/j.cmpb.2013.08.015
  2. Wookjin Choi, Tae-Sun Choi, “Automated Pulmonary Nodule Detection System in Computed Tomography Images: A Hierarchical Block Classification Approach”, Entropy, Vol. 15, No. 2, pp. 507-523, February 2013, doi: http://dx.doi.org/10.3390/e15020507
  3. Wookjin Choi, Tae-Sun Choi, “Genetic Programming-based feature transform and classification for the automatic detection of pulmonary nodules on computed tomography images”, Information Sciences, Vol. 212, pp. 57-78, December 2012, doi:http://dx.doi.org/10.1016/j.ins.2012.05.008

Published by Wookjin Choi

Assistant Professor Department of Radiation Oncology Thomas Jefferson University

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: