Conference proceeding
Three-dimensional murine airway segmentation in micro-CT images
Proceedings of SPIE, Vol.6511(1), pp.651105-6511010
Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
03/08/2007
DOI: 10.1117/12.711213
Abstract
Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.
Details
- Title: Subtitle
- Three-dimensional murine airway segmentation in micro-CT images
- Creators
- Lijun Shi - University of IowaJacqueline Thiesse - University of IowaGeoffrey McLennan - University of IowaEric A Hoffman - University of IowaJoseph M Reinhardt - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.6511(1), pp.651105-6511010
- Conference
- Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
- DOI
- 10.1117/12.711213
- ISSN
- 0277-786X
- Language
- English
- Date published
- 03/08/2007
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Internal Medicine; Radiology
- Record Identifier
- 9984197120002771
Metrics
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