Journal Title : International Journal of Modern Trends in Engineering and Science
Author’s Name : Athul R S | Shally K
Volume 02 Issue 11 Year 2015
ISSN no: 2348-3121
Page no: 44-47
Abstract— High-resolution X-ray computed tomography (CT) imaging is widely used for clinical pulmonary applications. The lung function varies regionally. Because diseases in the pulmonary region is usually not uniformly distributed in the lungs, it is efficient while studying the lungs on lobe- by-lobe basis. Automated extraction of lung lobes provides a foundation for computerized analysis of computed tomography scans of the chest. Segmentation of the pulmonary lobes is relevant in clinical practice and particularly challenging for cases with some diseases like localized emphysema or incomplete fissures. A method for automatic segmentation of pulmonary lobes from computed tomography scans of human chest is presented in this paper. The work starts with lung segmentation from the CT images based on region growing and standard image processing techniques. A completely automatic and faster method is presented to segment the lungs, lobes and pulmonary segments from chest CT scans in this work. A cost image for the clustering is computed by combining information from pulmonary vessels, bronchi, and fissures. A faster segmentation method is presented which performs Accelerated K-means clustering on the cost image of computed tomography (CT) scans to subdivide the lungs into lobes.
Keywords— Lobe segmentation; computed tomography; Accelerated K-means
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