Abstract
We were able to efficiently remove the morphological artifact of the fiber bundle based endo-microscopy and improve the featured patterns within the object image acquired by using non-invasive near infrared optical coherence tomography. Our image reconstruction methodology starts to estimate the original shape from the regions that are directly damaged from the en face image which contains significant image degradation by the pixelation of numerous imaging fiber units. Then we have iteratively extended the neighbor areas from the initial status so that we can successfully estimate the original shape of the missing pattern.
| Original language | English |
|---|---|
| Title of host publication | 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 |
| Pages | 84-85 |
| Number of pages | 2 |
| DOIs | |
| Publication status | Published - 2013 May 17 |
| Event | 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 - Gangwon Province, Korea, Republic of Duration: 2013 Feb 18 → 2013 Feb 20 |
Other
| Other | 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 |
|---|---|
| Country | Korea, Republic of |
| City | Gangwon Province |
| Period | 13/2/18 → 13/2/20 |
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Keywords
- Endoscopy
- Image restoration
- Optical Coherence Tomography
- Optical fibers
- Pattern recognition
ASJC Scopus subject areas
- Human-Computer Interaction
Cite this
Learning Markov random field image prior for pixelation removal of fiber microscopy using sparse coding based on Bayesian framework. / Lee, Cheon Yang; Han, Jae Ho.
2013 International Winter Workshop on Brain-Computer Interface, BCI 2013. 2013. p. 84-85 6506639.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Learning Markov random field image prior for pixelation removal of fiber microscopy using sparse coding based on Bayesian framework
AU - Lee, Cheon Yang
AU - Han, Jae Ho
PY - 2013/5/17
Y1 - 2013/5/17
N2 - We were able to efficiently remove the morphological artifact of the fiber bundle based endo-microscopy and improve the featured patterns within the object image acquired by using non-invasive near infrared optical coherence tomography. Our image reconstruction methodology starts to estimate the original shape from the regions that are directly damaged from the en face image which contains significant image degradation by the pixelation of numerous imaging fiber units. Then we have iteratively extended the neighbor areas from the initial status so that we can successfully estimate the original shape of the missing pattern.
AB - We were able to efficiently remove the morphological artifact of the fiber bundle based endo-microscopy and improve the featured patterns within the object image acquired by using non-invasive near infrared optical coherence tomography. Our image reconstruction methodology starts to estimate the original shape from the regions that are directly damaged from the en face image which contains significant image degradation by the pixelation of numerous imaging fiber units. Then we have iteratively extended the neighbor areas from the initial status so that we can successfully estimate the original shape of the missing pattern.
KW - Endoscopy
KW - Image restoration
KW - Optical Coherence Tomography
KW - Optical fibers
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=84877689359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877689359&partnerID=8YFLogxK
U2 - 10.1109/IWW-BCI.2013.6506639
DO - 10.1109/IWW-BCI.2013.6506639
M3 - Conference contribution
AN - SCOPUS:84877689359
SN - 9781467359733
SP - 84
EP - 85
BT - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
ER -