[day-27] U-net Experiments (3) - performance 2

前言

除了 EM segmentatation challenge 比赛之外，还有参加了另外一个比赛 ISBI cell tracking challenge，应用了两个资料集。
(1) PhC-U373
(2) DIC-HeLa

performance 2

We also applied the u-net to a cell segmentation task in light microscopic images. This segmenation task is part of the ISBI cell tracking challenge 2014 and 2015 [10,13].

说明了还去参加了什麽样的比赛。

The first data set “PhC-U373”2 contains Glioblastoma-astrocytoma U373 cells on a polyacrylimide substrate recorded by phase contrast microscopy (see Figure 4a,b and Supp. Material).

细胞的细节

It contains 35 partially annotated training images. Here we achieve an average IOU (“intersection over union”) of 92%, which is significantly better than the second best algorithm with 83% (see Table 2).

火力展示环节。

The second data set “DIC-HeLa”3 are HeLa cells on a flat glass recorded by differential interference contrast (DIC) microscopy (see Figure 3, Figure 4c,d and Supp. Material). It contains 20 partially annotated training images. Here we achieve an average IOU of 77.5% which is significantly better than the second best algorithm with 46%.

火力展示环节2。

两种资料级的样子。

Concusion

论文终於快读完了，在实验阶段Unet没有多说废话，说明规则，直接说明自己有多强。

Reference

[0] U-net