Document Type
Article
Publication Date
4-1-2018
Journal
Journal of Medical Imaging (Bellingham)
Volume
5
Issue
2
First Page
026002
Last Page
026002
URL with Digital Object Identifier
https://doi.org/10.1117/1.JMI.5.2.026002
Abstract
We designed and generated pulmonary imaging biomarker pipelines to facilitate high-throughput research and point-of-care use in patients with chronic lung disease. Image processing modules and algorithm pipelines were embedded within a graphical user interface (based on the .NET framework) for pulmonary magnetic resonance imaging (MRI) and x-ray computed-tomography (CT) datasets. The software pipelines were generated using C++ and included: (1) inhaled
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Citation of this paper:
Guo, F., Capaldi, D., Kirby, M., Sheikh, K., Svenningsen, S., McCormack, D. G., Fenster, A., Parraga, G., & Canadian Respiratory Research Network (2018). Development of a pulmonary imaging biomarker pipeline for phenotyping of chronic lung disease. Journal of medical imaging (Bellingham, Wash.), 5(2), 026002. https://doi.org/10.1117/1.JMI.5.2.026002
Notes
This is the final published version of the following article: F. Guo et al. (2018). Development of a pulmonary imaging biomarker pipeline for phenotyping of chronic lung disease. Journal of Medical Imaging, 5(2), 026002, https://doi.org/10.1117/1.JMI.5.2.026002. This article is published and made openly available by SPIE.