Lung Image Analysis Framwork

A basic framework for pulmonary nodule detection and characterization in CT

Tested on LIDC-IDRI dataset (

  • 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:
  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:
  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:

Published by Wookjin Choi

Assistant Professor Department of Radiation Oncology Thomas Jefferson University

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