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. 2022 May 18;2(4):100171. doi: 10.1016/j.xops.2022.100171

Figure 1.

Figure 1

Overall computational workflow of the radiomic-based assessment of response to anti–VEGF therapy in patients with neovascular age-related macular degeneration using baseline OCT scans. The first step involves identifying and segmenting the OCT compartments (fluid and subretinal hyperreflective material [SHRM]) and the retinal tissue compartments (internal limiting membrane [ILM]-retinal pigment epithelium [RPE], and RPE–Bruch’s membrane [BM]). Texture-based radiomic features are extracted from the individual OCT and retinal tissue compartments using MATLAB version 2015a software. Feature statistics, which included median, standard deviation, skewness, and kurtosis, were calculated for each of the individual compartments. The top 8 features were determined using the minimum redundancy maximum relevance feature selection algorithm, followed by classification using 3-fold cross-validation. Unsupervised hierarchical clustering also was performed. EZ = ellipsoid zone.