TY - GEN
T1 - Self-assessment for optic disc segmentation
AU - Cheng, Jun
AU - Liu, Jiang
AU - Yin, Fengshou
AU - Lee, Beng Hai
AU - Wong, Damon Wing Kee
AU - Aung, Tin
AU - Cheng, Ching Yu
AU - Wong, Tien Yin
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Optic disc segmentation from retinal fundus image is a fundamental but important step in many applications such as automated glaucoma diagnosis. Very often, one method might work well on many images but fail on some other images and it is difficult to have a single method or model to cover all scenarios. Therefore, it is important to combine results from several methods to minimize the risk of failure. For this purpose, this paper computes confidence scores for three methods and combine their results for an optimal one. The experimental results show that the combined result from three methods is better than the results by any individual method. It reduces the mean overlapping error by 7.4% relatively compared with best individual method. Simultaneously, the number of failed cases with large overlapping errors is also greatly reduced. This is important to enhance the clinical deployment of the automated disc segmentation.
AB - Optic disc segmentation from retinal fundus image is a fundamental but important step in many applications such as automated glaucoma diagnosis. Very often, one method might work well on many images but fail on some other images and it is difficult to have a single method or model to cover all scenarios. Therefore, it is important to combine results from several methods to minimize the risk of failure. For this purpose, this paper computes confidence scores for three methods and combine their results for an optimal one. The experimental results show that the combined result from three methods is better than the results by any individual method. It reduces the mean overlapping error by 7.4% relatively compared with best individual method. Simultaneously, the number of failed cases with large overlapping errors is also greatly reduced. This is important to enhance the clinical deployment of the automated disc segmentation.
UR - http://www.scopus.com/inward/record.url?scp=84886568994&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2013.6610885
DO - 10.1109/EMBC.2013.6610885
M3 - Conference contribution
C2 - 24111072
AN - SCOPUS:84886568994
SN - 9781457702167
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5861
EP - 5864
BT - 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
T2 - 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Y2 - 3 July 2013 through 7 July 2013
ER -