Skip to main content
. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: IEEE Trans Med Imaging. 2021 Nov 30;40(12):3507–3518. doi: 10.1109/TMI.2021.3089547

TABLE I.

Results on the task of synaptic cleft detection of the CREMI open challenge. We summarize the results of the best models for the top 5 groups. Our group is DIVE, and our best models is CleftNet. A DOWNWARD ARROW ↓ is used to indicate that a lower metric value corresponds to better performance. An upward arrow ↑ is used to indicate that a higher metric value corresponds to better performance. These results are provide at the CREMI website [36].

Rank Group Model CREMI-score(↓) F1-score(↑)
1 DIVE CleftNet 57.73 0.831
4 CleftKing CleABC1 58.02 0.821
6 lbdl lb_thicc 59.04 0.810
9 3DEM BesA225 59.34 0.823
15 SDG Unet2 63.92 0.744