Type | Authors | Method | Year | Dataset | Noudle IoU (%) | Noudle dice (%) | Gland IoU (%) | Gland dice (%) |
---|---|---|---|---|---|---|---|---|
Semi-supervised | Kunapinun et al. [46] | StableSeg GAN | 2022 | Private | 82.0 | Â | Â | Â |
Weakly-supervised | Liu et al. [47] | U2F-GAN | 2021 | Private | Â | 87.0 | Â | Â |
 | Yu et al. [52] | New SSE-WSSN | 2022 | Private | 51.2 | 65.8 |  |  |
Interactive | Shahroudnejad et al. [48] | ResDUnet | 2021 | Private | Â | 82.0 | Â | Â |
 | Daulatabad et al. [53] | Modified U-Net (One-Click) | 2021 | Private |  | 84.0 |  |  |
 | Chu et al. [24] | MGU-Net | 2021 | Private | 91.5 | 95.8 |  |  |
U-Net based | Buda et al. [23] | U-Net (with caliper) | 2020 | Private | Â | 93.4 | Â | Â |
 | Liao et al. [54] | U2-Rnet | 2021 | Private | 80.8 | 88.0 | 34.2 | 47.4 |
 | Ataide et al. [55] | ResUNet | 2021 | Private | 76.7 | 85.7 |  |  |
 | Ajilisa et al. [56] | Hybrid Res-UNet3 | 2022 | DDTI | 58.8 | 74.1 |  |  |
 | Lin et al. [57] | N-shape network | 2022 | UTNI-2021 | 87.0 | 91.9 |  |  |
 | Nie et al. [49] | N-Net | 2022 | TNUI-2021 | 87.2 | 92.0 |  |  |
 |  |  |  | DDTI | 88.5 | 93.7 |  |  |
 | Li et al. [58] | BTNet | 2022 | Private | 81.0 | 89.2 |  |  |
 |  |  |  | DDTI | 65.4 | 75.7 |  |  |
 |  |  |  | BUI | 73.5 | 81.2 |  |  |
 | Yadav et al. [59] | Hybrid-UNet (DsF_EPSF) | 2022 | DDTI + USC | 86.6 | 93.2 |  |  |
DeepLab based | Webb et al. [50] | DeepLabv3+ based convolutional LSTM | 2021 | Private | 53.3 |  | 73.9 |  |
 | Sun et al. [60] | TNSNet | 2021 | Private |  | 85.3 |  |  |
Other | Ma et al. [18] | Deep CNN | 2017 | Private | 86.8 | 92.2 | Â | Â |
 | Kumar et al. [51] | MPCNN | 2020 | Private |  | 73.0 (64) 76.0 (78) |  | 87.0 (68) 91.0 (80) |
 | Hu et al. [61] | CNN | 2022 | Private |  | 83.0 |  |  |
 | Dai et al. [62] | SEV-Net | 2022 | DDTI |  | 95.7 |  |  |
 | Tao et al. [63] | LCA-Net | 2022 | TN3K | 71.2 | 82.1 |  |  |
 |  |  |  | TN-SCUI2020 | 82.7 | 90.3 |  |  |
U-Net based | Â | DSRU-Net (Ours) | Â | Private | 89.4 | 94.1 | 83.2 | 90.9 |