Awais Mansoor PhD, Presenter: Nothing to Disclose

Ulas Bagci PhD, MSc, Abstract Co-Author: Nothing to Disclose

Brent Foster, Abstract Co-Author: Nothing to Disclose

Ziyue Xu PhD, Abstract Co-Author: Nothing to Disclose

Jayaram K. Udupa PhD, Abstract Co-Author: Nothing to Disclose

Daniel Joseph Mollura MD, Abstract Co-Author: Nothing to Disclose

To identify the clinical importance of lung segmentation and explain why CT images are used to quantify lung pathology. To review the current state-of-the-art image segmentation approaches for pathological lungs from CT scans. To identify the challenges in pathological lung segmentation. To discuss the future of lung segmentation methods and explain how engineering advancements in CT plays a valuable role.

1. Introduction a. Lung disease b. Clinical importance of segmentation 2. Segmenting Lung Pathology from CT images a. Why use CT images? b. Lung disease or normal lungs—no difference 3. State-of-the-Art Segmentation Methods for CT Images a. CT-based attenuation correction methods b. Registration-assisted methods c. Registration-assisted image smoothing methods d. Graph-based methods e. Model-based methods 4. The Challenges of Segmenting Lung Pathology a. Image quality b. Time needed for analysis 5. Concluding Remarks and future trends in lung segmentation pathology  

Review the clinical importance of lung segmentation. Review state-of-the-art lung segmentation methods for CT images. Review the challenges of lung segmentation. Review the challenges of lung segmentation.

Mansoor, A, Bagci, U, Foster, B, Xu, Z, Udupa, J, Mollura, D, Pathological Lung Segmentation in Computed Tomography (CT) Images: Current Approaches, Challenges, and Future Trends.  Radiological Society of North America 2013 Scientific Assembly and Annual Meeting, December 1 - December 6, 2013 ,Chicago IL. http://archive.rsna.org/2013/13022525.html