Variational approach for segmentation of lung nodules

Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First,...

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Bibliographic Details
Main Authors: Farag, A. A., Abdelmunim, H., Graham, J., Elshazly, S., El-Mogy, S., El-Mogy, M., Falk, R., Al-Jafary, S., Mahdi, H., Milam, R.
Format: Conference Proceeding
Language:English
Subjects:
Computed tomography
Conferences
Image segmentation
Level set
Lungs
Shape
Online Access:Request full text
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Summary:Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets. The outline of the nodule region is further improved using the curvature characteristics of the segmentation boundary. We illustrate the effectiveness of this method for automatic segmentation of the Juxta-pleural nodules.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2011.6116038