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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Kidney Int. 2020 Aug 22;99(1):86–101. doi: 10.1016/j.kint.2020.07.044

Figure 9|. Examples of false positive and false negative deep learning (DL) segmentations on periodic acid–Schiff (PAS).

Figure 9|

(a) Glomerular unit: DL failed to detect a tangentially cut glomerular unit that does not have a typical round shape (red thick arrow). (b) Artery: section artifact generate a false positive (red thick arrows). (c) Arteries: black arrows show 2 arterioles missed by the pathologist but detected by DL. (d) Arteries: pathologists were instructed to segment artery when lumen was present; however, DL segmentation detected tangentially cut artery (thick black arrow) where only the medium was visible. (e) Peritubular capillaries: a long peritubular capillary reveals only partial DL segmentation at the pixel level. (f) Peritubular capillaries: DL network for peritubular capillaries detects a few glomerular capillaries (false positive; thick red arrow).