Abstract
In this paper we explore a method of segmentation of muscle interstitial adipose tissue (IAT) in MR images of the thigh. The objective is to apply the method towards research into biomarkers of osteoarthritis (OA). T1-weighted images of the thigh are intensity standardized through bias field correction and intensity normalization. IAT within the thigh muscles is then segmented using a threshold combined with morphological constraints applied on connected regions in the thresholded image. The morphological constraints can be adjusted to allow for highly sensitive or highly specific IAT segmentation. The use of the morphological constraints improved the specificity of IAT segmentation over a threshold segmentation method from 0.54 to 0.67, while retaining a nearly equivalent sensitivity of 0.82 compared to 0.84. We then present a preliminary statistical analysis to demonstrate the application of the automated IAT segmentation. Finally, we specify a protocol for further exploration of IAT by leveraging the massive imaging dataset of the Osteoarthritis Initiative (OAI).
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
| Subtitle of host publication | Engineering the Future of Biomedicine, EMBC 2009 |
| Publisher | IEEE Computer Society |
| Pages | 6360-6363 |
| Number of pages | 4 |
| ISBN (Print) | 9781424432967 |
| DOIs | |
| State | Published - Jan 1 2009 |
| Externally published | Yes |
| Event | 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States Duration: Sep 2 2009 → Sep 6 2009 |
Other
| Other | 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 |
|---|---|
| Country | United States |
| City | Minneapolis, MN |
| Period | 9/2/09 → 9/6/09 |
Fingerprint
ASJC Scopus subject areas
- Cell Biology
- Developmental Biology
- Biomedical Engineering
- Medicine(all)
Cite this
An automated method to detect interstitial adipose tissue in thigh muscles for patients with osteoarthritis. / Prescott, Jeffrey W.; Priddy, Mike; Best, Thomas; Pennell, Michael; Swanson, Mark S.; Haq, Furqan; Jackson, Rebecca D.; Gurcan, Metin N.
Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE Computer Society, 2009. p. 6360-6363 5333260.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An automated method to detect interstitial adipose tissue in thigh muscles for patients with osteoarthritis
AU - Prescott, Jeffrey W.
AU - Priddy, Mike
AU - Best, Thomas
AU - Pennell, Michael
AU - Swanson, Mark S.
AU - Haq, Furqan
AU - Jackson, Rebecca D.
AU - Gurcan, Metin N.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - In this paper we explore a method of segmentation of muscle interstitial adipose tissue (IAT) in MR images of the thigh. The objective is to apply the method towards research into biomarkers of osteoarthritis (OA). T1-weighted images of the thigh are intensity standardized through bias field correction and intensity normalization. IAT within the thigh muscles is then segmented using a threshold combined with morphological constraints applied on connected regions in the thresholded image. The morphological constraints can be adjusted to allow for highly sensitive or highly specific IAT segmentation. The use of the morphological constraints improved the specificity of IAT segmentation over a threshold segmentation method from 0.54 to 0.67, while retaining a nearly equivalent sensitivity of 0.82 compared to 0.84. We then present a preliminary statistical analysis to demonstrate the application of the automated IAT segmentation. Finally, we specify a protocol for further exploration of IAT by leveraging the massive imaging dataset of the Osteoarthritis Initiative (OAI).
AB - In this paper we explore a method of segmentation of muscle interstitial adipose tissue (IAT) in MR images of the thigh. The objective is to apply the method towards research into biomarkers of osteoarthritis (OA). T1-weighted images of the thigh are intensity standardized through bias field correction and intensity normalization. IAT within the thigh muscles is then segmented using a threshold combined with morphological constraints applied on connected regions in the thresholded image. The morphological constraints can be adjusted to allow for highly sensitive or highly specific IAT segmentation. The use of the morphological constraints improved the specificity of IAT segmentation over a threshold segmentation method from 0.54 to 0.67, while retaining a nearly equivalent sensitivity of 0.82 compared to 0.84. We then present a preliminary statistical analysis to demonstrate the application of the automated IAT segmentation. Finally, we specify a protocol for further exploration of IAT by leveraging the massive imaging dataset of the Osteoarthritis Initiative (OAI).
UR - http://www.scopus.com/inward/record.url?scp=77950987108&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950987108&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2009.5333260
DO - 10.1109/IEMBS.2009.5333260
M3 - Conference contribution
SN - 9781424432967
SP - 6360
EP - 6363
BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - IEEE Computer Society
ER -