2020-12-24 15:58:09 +08:00
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# U-Net: Convolutional Networks for Biomedical Image Segmentation
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## Introduction
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2021-01-11 13:35:09 +08:00
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[ALGORITHM]
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2020-12-24 15:58:09 +08:00
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```latex
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@inproceedings{ronneberger2015u,
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title={U-net: Convolutional networks for biomedical image segmentation},
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author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
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booktitle={International Conference on Medical image computing and computer-assisted intervention},
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pages={234--241},
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year={2015},
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organization={Springer}
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}
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```
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## Results and models
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| Backbone | Head | Dataset | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download |
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|--------|----------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| UNet-S5-D16 | FCN | DRIVE | 584x565 | 64x64 | 42x42 | 40000 | 0.680 | - | 78.67 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_64x64_40k_drive/unet_s5-d16_64x64_40k_drive_20201223_191051-9cd163b8.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_64x64_40k_drive/unet_s5-d16_64x64_40k_drive-20201223_191051.log.json) |
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| UNet-S5-D16 | FCN | STARE | 605x700 | 128x128 | 85x85 | 40000 | 0.968 | - | 81.02 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_stare/unet_s5-d16_128x128_40k_stare_20201223_191051-e5439846.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_stare/unet_s5-d16_128x128_40k_stare-20201223_191051.log.json) |
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| UNet-S5-D16 | FCN | CHASE_DB1 | 960x999 | 128x128 | 85x85 | 40000 | 0.968 | - | 80.24 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_chase_db1/unet_s5-d16_128x128_40k_chase_db1_20201223_191051-8b16ca0b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_chase_db1/unet_s5-d16_128x128_40k_chase_db1-20201223_191051.log.json) |
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| UNet-S5-D16 | FCN | HRF | 2336x3504 | 256x256 | 170x170 | 40000 | 2.525 | - | 79.45 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_256x256_40k_hrf/unet_s5-d16_256x256_40k_hrf_20201223_173724-d89cf1ed.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_256x256_40k_hrf/unet_s5-d16_256x256_40k_hrf-20201223_173724.log.json) |
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