Chapter title |
Emphysema Quantification on Cardiac CT Scans Using Hidden Markov Measure Field Model: The MESA Lung Study
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Chapter number | 72 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016
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Published in |
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, October 2016
|
DOI | 10.1007/978-3-319-46723-8_72 |
Pubmed ID | |
Book ISBNs |
978-3-31-946722-1, 978-3-31-946723-8
|
Authors |
Jie Yang, Elsa D. Angelini, Pallavi P. Balte, Eric A. Hoffman, Colin O. Wu, Bharath A. Venkatesh, R. Graham Barr, Andrew F. Laine, Yang, Jie, Angelini, Elsa D., Balte, Pallavi P., Hoffman, Eric A., Wu, Colin O., Venkatesh, Bharath A., Barr, R. Graham, Laine, Andrew F. |
Abstract |
Cardiac computed tomography (CT) scans include approximately 2/3 of the lung and can be obtained with low radiation exposure. Large cohorts of population-based research studies reported high correlations of emphysema quantification between full-lung (FL) and cardiac CT scans, using thresholding-based measurements. This work extends a hidden Markov measure field (HMMF) model-based segmentation method for automated emphysema quantification on cardiac CT scans. We show that the HMMF-based method, when compared with several types of thresholding, provides more reproducible emphysema segmentation on repeated cardiac scans, and more consistent measurements between longitudinal cardiac and FL scans from a diverse pool of scanner types and thousands of subjects with ten thousands of scans. |
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Mendeley readers
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Other | 3 | 20% |
Researcher | 3 | 20% |
Student > Master | 1 | 7% |
Professor | 1 | 7% |
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Unknown | 1 | 7% |
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Unknown | 3 | 20% |