Automatic Lung Segmentation With Juxta-Pleural Nodule Identification Using Active Contour Model and Bayesian Approach

@inproceedings{Chung2018AutomaticLS,
  title={Automatic Lung Segmentation With Juxta-Pleural Nodule Identification Using Active Contour Model and Bayesian Approach},
  author={HeeWon Chung and Hoon Ko and Se Jeong Jeon and Kwon-Ha Yoon and Jinseok Lee},
  booktitle={IEEE Journal of Translational Engineering in Health and Medicine},
  year={2018}
}
Objective: chest computed tomography (CT) images and their quantitative analyses have become increasingly important for a variety of purposes, including lung parenchyma density analysis, airway analysis, diaphragm mechanics analysis, and nodule detection for cancer screening. Lung segmentation is an important prerequisite step for automatic image analysis. We propose a novel lung segmentation method to minimize the juxta-pleural nodule issue, a notorious challenge in the applications. Method… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 46 REFERENCES

Guidelines for management of incidental pulmonary nodules detected on CT images: From the Fleischner Society 2017

H.MacMahon
  • Radiology, vol. 284, no. 1, pp. 228–243, 2017.
  • 2017
VIEW 1 EXCERPT

Computer-aided diagnosis (CAD) of subsolid nodules: Evaluation of a commercial CAD system

J. Benzakoun
  • Eur. J. Radiol., vol. 85, no. 10, pp. 1728–1734, 2016.
  • 2016
VIEW 1 EXCERPT

Automatic CT image segmentation of the lungs with an iterative Chan-Vese algorithm

  • 2015 International Conference on Informatics, Electronics & Vision (ICIEV)
  • 2015
VIEW 2 EXCERPTS

Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends.

  • Radiographics : a review publication of the Radiological Society of North America, Inc
  • 2015
VIEW 1 EXCERPT