Journal article
Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images
IEEE transactions on medical imaging, Vol.20(6), pp.490-498
2001
DOI: 10.1109/42.929615
PMID: 11437109
Abstract
Segmentation of pulmonary X-ray computed tomography (CT) images is a precursor to most pulmonary image analysis applications. This paper presents a fully automatic method for identifying the lungs in three-dimensional (3-D) pulmonary X-ray CT images. The method has three main steps. First, the lung region is extracted from the CT images by gray-level thresholding. Then, the left and right lungs are separated by identifying the anterior and posterior junctions by dynamic programming. Finally, a sequence of morphological operations is used to smooth the irregular boundary along the mediastinum in order to obtain results consistent with those obtained by manual analysis, in which only the most central pulmonary arteries are excluded from the lung region. The method has been tested by processing 3-D CT data sets from eight normal subjects, each imaged three times at biweekly intervals with lungs at 90% vital capacity. We present results by comparing our automatic method to manually traced borders from two image analysts. Averaged over all volumes, the root mean square difference between the computer and human analysis is 0.8 pixels (0.54 mm). The mean intrasubject change in tissue content over the three scans was 2.75% +/- 2.29% (mean +/- standard deviation).
Details
- Title: Subtitle
- Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images
- Creators
- SHIYING HU - University of IowaEric A Hoffman - University of IowaJoseph M Reinhardt - University of Iowa
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.20(6), pp.490-498
- DOI
- 10.1109/42.929615
- PMID
- 11437109
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Language
- English
- Date published
- 2001
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984197150102771
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