Automated lung segmentation on digital tomosynthesis images with complex method |
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| Bence Tilk |
- Abstract:
- For lung screening the most common method is chest radiography, which produces summation images without giving any depth information about the lung. Computed Tomography (CT) creates excellent slice images, which give volume data that makes CT a more sensitive nodule detection system. However CT has disadvantages, it is too expensive and it’s x-ray emission is too high to be used as an everyday screening method. Digital tomosynthesis (DTS), as a relatively new chest imaging modality, can be positioned between chest radiography and CT. While it produces slice images of the chest similarly to CT, its slice thickness is larger, it creates a bit more blurred slices, it has much lower radiation than CT. This blurring makes it hard to segment the lung areas automatically, which is essential for an efficient Computeraided Diagnosis system. The paper proposes a combined method, which starts from a previously published approach, extends it using snake methods and adjacent images’ segmentation information to improve lung segmentation. Experiments show that the combination of methods reduces the incorrectly segmented lung region.
- Keywords:
- medical imaging, digital tomosynthesis, lung segmentation, computer-aided diagnosis.
- Download:
- IMEKO-TC4-2016-27.pdf
- DOI:
- -
- Event details
- IMEKO TC:
- TC4
- Event name:
- TC4 Symposium 2016
- Title:
21st IMEKO TC4 Symposium on Measurements of Electrical Quantities (together with 19th TC4 International Workshop on ADC and DCA Modeling and Testing, IWADC)
"Understanding the World through Electrical and Electronic Measurement"- Place:
- Budapest, HUNGARY
- Time:
- 07 September 2016 - 09 September 2016