Abstract
A completely automated algorithm is presented which is capable of identifying both the right- and left-lung fields on digitized chest radiographic images. The algorithm is tested on a sample of 802 chest images against lung fields drawn by a human observer. The average accuracies are found to be 0.957±0.003 and 0.960±0.003 for right- and left-lung regions, respectively. To put them into perspective, the results are compared to several other simple segmentation techniques. These include a comparison of two sets of lung fields drawn by the human observer at different times which yielded accuracies of 0.967±0.005 and 0.967±0.004 for right- and left-lung regions, respectively.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 183-192 |
| Number of pages | 10 |
| Journal | Medical Physics |
| Volume | 22 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1995 |
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ASJC Scopus subject areas
- Biophysics
Cite this
A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images. / Duryea, J.; Boone, John M.
In: Medical Physics, Vol. 22, No. 2, 1995, p. 183-192.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images
AU - Duryea, J.
AU - Boone, John M
PY - 1995
Y1 - 1995
N2 - A completely automated algorithm is presented which is capable of identifying both the right- and left-lung fields on digitized chest radiographic images. The algorithm is tested on a sample of 802 chest images against lung fields drawn by a human observer. The average accuracies are found to be 0.957±0.003 and 0.960±0.003 for right- and left-lung regions, respectively. To put them into perspective, the results are compared to several other simple segmentation techniques. These include a comparison of two sets of lung fields drawn by the human observer at different times which yielded accuracies of 0.967±0.005 and 0.967±0.004 for right- and left-lung regions, respectively.
AB - A completely automated algorithm is presented which is capable of identifying both the right- and left-lung fields on digitized chest radiographic images. The algorithm is tested on a sample of 802 chest images against lung fields drawn by a human observer. The average accuracies are found to be 0.957±0.003 and 0.960±0.003 for right- and left-lung regions, respectively. To put them into perspective, the results are compared to several other simple segmentation techniques. These include a comparison of two sets of lung fields drawn by the human observer at different times which yielded accuracies of 0.967±0.005 and 0.967±0.004 for right- and left-lung regions, respectively.
UR - http://www.scopus.com/inward/record.url?scp=0028921567&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0028921567&partnerID=8YFLogxK
U2 - 10.1118/1.597539
DO - 10.1118/1.597539
M3 - Article
C2 - 7565349
AN - SCOPUS:0028921567
VL - 22
SP - 183
EP - 192
JO - Medical Physics
JF - Medical Physics
SN - 0094-2405
IS - 2
ER -