TY - GEN
T1 - A fully automated spinal cord segmentation
AU - Subramanya Jois, S. P.
AU - Sridhar, Harsha
AU - Harish Kumar, J. R.
PY - 2019/2/20
Y1 - 2019/2/20
N2 - Segmentation of the spinal cord region is an imperative step in the automated analysis of neurological ailments such as multiple sclerosis. Multiple studies demonstrated the connection between progression of neurological diseases and measurements identifying with spinal cord atrophy and changes to its structure. Segmentation of spinal cord region manually or semi-automatically, can be conflicting and tedious for large datasets. We present a novel automated method, that segments the spinal cord region, utilizing circular active discs and region growth algorithm. The proposed method is validated on the Visible Human Project dataset. The results with regards to sensitivity, specificity, accuracy, Jaccard index, and Dice coefficient were 97.23%, 100%, 99.76%, 96.83%, and 98.65%, respectively. The results were observed to be highly precise in comparison to expert outlines.
AB - Segmentation of the spinal cord region is an imperative step in the automated analysis of neurological ailments such as multiple sclerosis. Multiple studies demonstrated the connection between progression of neurological diseases and measurements identifying with spinal cord atrophy and changes to its structure. Segmentation of spinal cord region manually or semi-automatically, can be conflicting and tedious for large datasets. We present a novel automated method, that segments the spinal cord region, utilizing circular active discs and region growth algorithm. The proposed method is validated on the Visible Human Project dataset. The results with regards to sensitivity, specificity, accuracy, Jaccard index, and Dice coefficient were 97.23%, 100%, 99.76%, 96.83%, and 98.65%, respectively. The results were observed to be highly precise in comparison to expert outlines.
UR - http://www.scopus.com/inward/record.url?scp=85063078605&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063078605&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2018.8646682
DO - 10.1109/GlobalSIP.2018.8646682
M3 - Conference contribution
AN - SCOPUS:85063078605
T3 - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
SP - 524
EP - 528
BT - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
Y2 - 26 November 2018 through 29 November 2018
ER -
