14 February 2012 Automatic lung lobe segmentation of COPD patients using iterative B-spline fitting
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Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83140W (2012); doi: 10.1117/12.910869
Event: SPIE Medical Imaging, 2012, San Diego, California, United States
Abstract
We present an automatic lung lobe segmentation algorithm for COPD patients. The method enhances fissures, removes unlikely fissure candidates, after which a B-spline is fitted iteratively through the remaining candidate objects. The iterative fitting approach circumvents the need to classify each object as being part of the fissure or being noise, and allows the fissure to be detected in multiple disconnected parts. This property is beneficial for good performance in patient data, containing incomplete and disease-affected fissures. The proposed algorithm is tested on 22 COPD patients, resulting in accurate lobe-based densitometry, and a median overlap of the fissure (defined 3 voxels wide) with an expert ground truth of 0.65, 0.54 and 0.44 for the three main fissures. This compares to complete lobe overlaps of 0.99, 0.98, 0.98, 0.97 and 0.87 for the five main lobes, showing promise for lobe segmentation on data of patients with moderate to severe COPD.
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D. P. Shamonin, M. Staring, M. E. Bakker, C. Xiao, J. Stolk, J. H. C. Reiber, B. C. Stoel, "Automatic lung lobe segmentation of COPD patients using iterative B-spline fitting", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83140W (14 February 2012); doi: 10.1117/12.910869; http://dx.doi.org/10.1117/12.910869
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KEYWORDS
Lung

Chronic obstructive pulmonary disease

Image segmentation

Tissues

Computed tomography

Densitometry

Emphysema

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