Abstract
Accurate definition of the central-chest vasculature from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. For instance, the aorta and pulmonary artery help in automatic definition of the Mountain lymph-node stations for lung-cancer staging. This work presents a system for defining major vascular structures in the central chest. The system provides automatic methods for extracting the aorta and pulmonary artery and semi-automatic methods for extracting the other major central chest arteries/veins, such as the superior vena cava and azygos vein. Automatic aorta and pulmonary artery extraction are performed by model fitting and selection. The system also extracts certain vascular structure information to validate outputs. A semi-automatic method extracts vasculature by finding the medial axes between provided important sites. Results of the system are applied to lymph-node station definition and guidance of bronchoscopic biopsy.
| Original language | English (US) |
|---|---|
| Title of host publication | Medical Imaging 2009 - Image Processing |
| DOIs | |
| State | Published - 2009 |
| Event | Medical Imaging 2009 - Image Processing - Lake Buena Vista, FL, United States Duration: Feb 8 2009 → Feb 10 2009 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 7259 |
| ISSN (Print) | 1605-7422 |
Other
| Other | Medical Imaging 2009 - Image Processing |
|---|---|
| Country/Territory | United States |
| City | Lake Buena Vista, FL |
| Period | 2/8/09 → 2/10/09 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics
- Biomaterials
- Radiology Nuclear Medicine and imaging
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