TY - GEN
T1 - A study on automated segmentation of retinal layers in optical coherence tomography images
AU - Ngo, Lua
AU - Yih, Geown
AU - Ji, Seungbae
AU - Han, Jae Ho
N1 - Funding Information:
This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF-2013R1A1A2062448).
Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/20
Y1 - 2016/4/20
N2 - The great achievements in both advanced optical coherence tomography (OCT) technique and computational methods contribute an undeniable tools in clinical diagnosis, especially in ophthalmological diseases diagnosis. Motived to catch up the state of art, the contemporary OCT image segmentation methods widely applied are reviewed and systematically summarized.
AB - The great achievements in both advanced optical coherence tomography (OCT) technique and computational methods contribute an undeniable tools in clinical diagnosis, especially in ophthalmological diseases diagnosis. Motived to catch up the state of art, the contemporary OCT image segmentation methods widely applied are reviewed and systematically summarized.
KW - Biomedical optical imaging
KW - Image segmentation
KW - Medical image processing
KW - Optical coherence tomography
KW - Retina
UR - http://www.scopus.com/inward/record.url?scp=84969217922&partnerID=8YFLogxK
U2 - 10.1109/IWW-BCI.2016.7457465
DO - 10.1109/IWW-BCI.2016.7457465
M3 - Conference contribution
AN - SCOPUS:84969217922
T3 - 4th International Winter Conference on Brain-Computer Interface, BCI 2016
BT - 4th International Winter Conference on Brain-Computer Interface, BCI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Winter Conference on Brain-Computer Interface, BCI 2016
Y2 - 22 February 2016 through 24 February 2016
ER -