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Aaron Y Lee, Adnan Tufail; Mechanical Turk based system for macular OCT segmentation. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4787.
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© ARVO (1962-2015); The Authors (2016-present)
The current generation of automated OCT segmentation software struggles with certain disease features such as subretinal fibrosis in neovascular AMD where OCT plays a critical role in management. In addition, precise segmentation of macular features such as subretinal or intraretinal fluid volume could lead to sensitive endpoints for clinical trials. We sought to achieve highly reliable segmentation by designing a novel system for distributed OCT segmentation over a scalable, human based infrastructure and to show proof of concept results.
Representative images showing the segmentation are shown (Figure 1A). Average time to completion of both lines was 30.83 seconds (SD = 7.30 seconds). The total cost of the segmentation per macular OCT was $0.18. More than 9200 data points were collected over the 18 retinal OCT images. Pearson's correlation of inter-rater reliability was 0.995 (p < 0.0001) and coefficient of determination was 0.991. Bland-Altman plots were calculated to estimate inter-rater agreement (Figure 1B).
Mechanical Turk provides a cost-effective, scalable, high-availability infrastructure for manual segmentation of OCT images. The resulting images could be recombined for high resolution 3D analysis and segmentation of OCT features that are difficult for automated algorithms could be achieved using this platform.
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