Performance evaluation of automated segmentation software on optical coherence tomography volume data.

ABSTRACT: Over the past two decades a significant number of OCT segmentation approaches have been proposed in the literature. Each methodology has been conceived for and/or evaluated using specific datasets that do not reflect the complexities of the majority of widely available retinal features observed in clinical settings. In addition, there does not exist an appropriate OCT dataset with ground truth that reflects the realities of everyday retinal features observed in clinical settings. While the need for unbiased performance evaluation of automated segmentation algorithms is obvious, the validation process of segmentation algorithms have been usually performed by comparing with manual labelings from each study and there has been a lack of common ground truth. Therefore, a performance comparison

SUBMITTER: Tian J 

PROVIDER: S-EPMC5025289 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature