TY - GEN
T1 - Automated Segmentation and Extraction of Posterior Eye Segment using OCT Scans
AU - Hassan, Bilal
AU - Hassan, Taimur
AU - Ahmed, Ramsha
AU - Qin, Shiyin
AU - Werghi, Naoufel
N1 - Funding Information:
This work is supported by a research fund from Khalifa University. Ref: CIRA-2019-047 and the Abu Dhabi Department of Education and Knowledge (ADEK), Ref: AARE19-156. †Co-first Authors, *Corresponding Author, Email: [email protected]
Funding Information:
This work is supported by a research fund from Khalifa University. Ref: CIRA-2019-047 and the Abu Dhabi Department of Education and Knowledge (ADEK), Ref: AARE19-156.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper proposes an automated method for the segmentation and extraction of the posterior segment of the human eye, including the vitreous, retina, choroid, and sclera compartments, using multi-vendor optical coherence tomography (OCT) scans. The proposed method works in two phases. First extracts the retinal pigment epithelium (RPE) layer by applying the adaptive thresholding technique to identify the retina-choroid junction. Then, it exploits the structure tensor guided approach to extract the inner limiting membrane (ILM) and the choroidal stroma (CS) layers, locating the vitreous-retina and choroid-sclera junctions in the candidate OCT scan. Furthermore, these three junction boundaries are utilized to conduct posterior eye compartmentalization effectively for both healthy and disease eye OCT scans. The proposed framework is evaluated over 1000 OCT scans, where it obtained the mean intersection over union (IoU) and mean Dice similarity coefficient (DSC) scores of 0.874 and 0.930, respectively.
AB - This paper proposes an automated method for the segmentation and extraction of the posterior segment of the human eye, including the vitreous, retina, choroid, and sclera compartments, using multi-vendor optical coherence tomography (OCT) scans. The proposed method works in two phases. First extracts the retinal pigment epithelium (RPE) layer by applying the adaptive thresholding technique to identify the retina-choroid junction. Then, it exploits the structure tensor guided approach to extract the inner limiting membrane (ILM) and the choroidal stroma (CS) layers, locating the vitreous-retina and choroid-sclera junctions in the candidate OCT scan. Furthermore, these three junction boundaries are utilized to conduct posterior eye compartmentalization effectively for both healthy and disease eye OCT scans. The proposed framework is evaluated over 1000 OCT scans, where it obtained the mean intersection over union (IoU) and mean Dice similarity coefficient (DSC) scores of 0.874 and 0.930, respectively.
KW - Choroid
KW - Extraction
KW - Optical Coherence Tomography (OCT)
KW - Posterior Eye Segment
KW - Retina
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=85118629362&partnerID=8YFLogxK
U2 - 10.1109/ICRAI54018.2021.9651403
DO - 10.1109/ICRAI54018.2021.9651403
M3 - Conference contribution
AN - SCOPUS:85118629362
T3 - 2021 International Conference on Robotics and Automation in Industry, ICRAI 2021
BT - 2021 International Conference on Robotics and Automation in Industry, ICRAI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Robotics and Automation in Industry, ICRAI 2021
Y2 - 26 October 2021 through 27 October 2021
ER -