This repository provides code for paper "BlazeNeo: Blazing fast polyp segmentation and neoplasm detection" in IEEE Access, vol. 10, pp. 43669-43684, 2022.
- Real-time Speed: Our method, name BlazeNeo, can efficiently perform polyp segmentation and neoplasm detection from polyp videos with real-time speed (~81.5 FPS) on a single NVIDIA Tesla V100 GPU.
- Cutting-edge Performance: Extensive experiments on the newly collected NeoPolyp dataset and comparisons to existing models. Moreover, we measure model latency and throughput on dedicated hardware in a setting similar to a real-life deployment.
Download our public dataset BKAI-IGH NeoPolyp-Small for your own experiments.
pip install -r requirements.txt
python train.py
python eval.py
python infer.py
Performance metrics on the NeoPolyp-Clean test set for ColonSegNet, U-Net, DDANet, DoubleU-Net, PraNet, HardNet-MSEG, NeoUNet and BlazeNeo.
Method | Diceseg | Dice non | Dice neo | FPS | Parameters | GFLOPs |
---|---|---|---|---|---|---|
ColonSegNet | 0.738 | 0.505 | 0.732 | 44.9 | 5,010,000 | 64,84 |
U-Net | 0.785 | 0.525 | 0.773 | 69.6 | 31,043,651 | 103,59 |
DDANet | 0.813 | 0.578 | 0.802 | 46.2 | 6,840,000 | 31,45 |
DoubleU-Net | 0.837 | 0.621 | 0.832 | 43.2 | 18,836,804 | 83,62 |
HarDNet-MSEG | 0.883 | 0.659 | 0.869 | 77.1 | 17,424,031 | 11,38 |
PraNet | 0.895 | 0.705 | 0.873 | 55.6 | 30,501,341 | 13,11 |
NeoUNet | 0.911 | 0.720 | 0.889 | 68.3 | 38,288,397 | 39,88 |
BlazeNeo (Ours) | 0.904 | 0.717 | 0.885 | 81.5 | 17,143,324 | 11.06 |
Qualitative comparison of the proposed method with other baseline methods: (a) image, (b) ground truth, (c) BlazeNeo (Ours), (d) NeoUNet, (e) PraNet, (f) HarDNet-MSEG, (g) UNet, (h) Double U-Net, (i) DDANet, and (j) ColonSegNet.
This work was funded by Vingroup Innovation Foundation (VINIF) under project code VINIF.2020.DA17. We thank IGH for collecting and annotating the data.
Please cite our work if you find it useful:
@ARTICLE{blazeneo2022,
author={An, Nguyen S. and Lan, Phan N. and Hang, Dao V. and Long, Dao V. and Trung, Tran Q. and Thuy, Nguyen T. and Sang, Dinh V.},
journal={IEEE Access},
title={BlazeNeo: Blazing Fast Polyp Segmentation and Neoplasm Detection},
year={2022},
volume={10},
pages={43669-43684}
}
If you want to improve the usability or any piece of advice, please feel free to contact me directly ([email protected])